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  • 151.
    Johansson, Jonathan
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Wikdahl, Daniel
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Human identification with radar2016Självständigt arbete på grundnivå (högskoleexamen), 180 hpStudentuppsats (Examensarbete)
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  • 152.
    Johansson, Oscar
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Andersson, Gustav
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Smart Greenhouse: A microcontroller based architecture for autonomous and remote control2020Självständigt arbete på grundnivå (högskoleexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Dyra och komplexa automatiserade växthussystem är vanligt förekommande inom industrin för hortikultur. Parallellt har populariteten för "Smart Home" system för hemautomatisering radikalt ökat. Målet med detta projekt är att kombinera klimatoptimiseringsmöjligheterna hos industriella system med lättanvändligheten hos system för hemautomatisering. Detta projekt fokuserar specifikt på designen och implementationen av de elektriska och mekaniska krav som ställs på ett "smart greenhouse system". Detta innefattar; val av komponenter såsom sensorer, aktuatorer samt styrenhet men även sammankopplingen mellan dessa komponenter och utvecklingen av mjukvara till reglersystemet, som i sin tur syftar till automatiseringen i växthuset. Systemet är baserat på en WiFi-uppkopplad mikrokontroller. Parametrar som monitoreras är; temperatur, luftfuktighet och vindhastighet. Bevattning kontrolleras av en magnetventil och kan schemaläggas för bevattning i önskade intervall. Ventilering och temperaturoptimisering sker genom kontroll av taklucka med hjälp av ett linjärt ställdon samt kontroll av ett värmeelement. Resultatet demonstrerar ett pålitligt och punktligt system med låg energiförbrukning. Prototypen som utvecklats kan installeras i både nya och befintliga växthus. Funktionaliteterna kan smidigt fjärrkontrolleras och monitoreras från en android applikation. Den totala kostnaden för de komponenter som använts var runt 4500 kr. Vidareutveckling vad gäller skalbarhet för att sömlöst lägga till komponenter och funktionaliteter bör övervägas. För ytterligare minskad energiförbrukning med hjälp av klimatoptimering kan väderprognos adderas som en parameter.

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  • 153.
    Johnsson, Dennis
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Bengtsson, Jerker
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Svensson, Bertil
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Two-level Reconfigurable Architecture for High-Performance Signal Processing2004Ingår i: ERSA'04, The 2004 International Conference on Engineering of Reconfigurable Systems and Algorithms: The 2004 International MultiConference in Computer Science and Computer Engineering / [ed] Toomas P. Plaks, Arthens: CSREA Press, 2004, s. 177-183Konferensbidrag (Refereegranskat)
    Abstract [en]

    High speed signal processing is often performed as a pipeline of functions on streams or blocks of data. In order to obtain both flexibility and performance, parallel, reconfigurable array structures are suitable for such processing. The array topology can be used both on the micro and macro-levels, i.e. both when mapping a function on a fine-grained array structure and when mapping a set of functions on different nodes in a coarse-grained array. We outline an architecture on the macro-level as well as explore the use of an existing, commercial, word level reconfigurable architecture on the micro-level. We implement an FFT algorithm in order to determine how much of the available resources are needed for controlling the computations. Having no program memory and instruction sequencing available, a large fraction, 70%, of the used resources is used for controlling the computations, but this is still more efficient than having statically dedicated resources for control. Data can stream through the array at maximum I/O rate, while computing FFTs. The paper also shows how pipelining of the FFT algorithm over a two-level reconfigurable array of arrays can be done in various ways, depending on the application demands.

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  • 154.
    Josse, Elias
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Nerborg, Amanda
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Hernandez-Diaz, Kevin
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    In-Bed Person Monitoring Using Thermal Infrared Sensors2021Konferensbidrag (Refereegranskat)
    Abstract [en]

    The world is expecting an aging population and shortage of healthcare professionals. This poses the problem of providing a safe and dignified life for the elderly. Technological solutions involving cameras can contribute to safety, comfort and efficient emergency responses, but they are invasive of privacy. We use ’Griddy’, a prototype with a Panasonic Grid-EYE, a low- resolution infrared thermopile array sensor, which offers more privacy. Mounted over a bed, it can determine if the user is on the bed or not without human interaction. For this purpose, two datasets were captured, one (480 images) under constant conditions, and a second one (200 images) under different variations such as use of a duvet, sleeping with a pet, or increased room temperature. We test three machine learning algorithms: Support Vector Machines (SVM), k-Nearest Neighbors (k-NN) and Neural Network (NN). With 10-fold cross validation, the highest accuracy in the main dataset is for both SVM and k-NN (99%). The results with variable data show a lower reliability under certain circumstances, highlighting the need of extra work to meet the challenge of variations in the environment.

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  • 155.
    Juneby, Hans
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Can, Mikael
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Newtons andra vagn2015Självständigt arbete på grundnivå (högskoleexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    Ett problem för den grundläggande fysikundervisningen i skolan är att tyngdkraften ständigt stör experiment och demonstrationer, vilket gör det svårt för eleverna att förstå Newtons första och andra lag. Målet med projektet är att förbättra fysikundervisningen på högskolans bastermin. För att lösa problemet skapade vi en demonstrationsanläggning som effektivt demonstrerar inertialsystem och Newtons andra lag genom att köra ett specialkonstruerat tåg med konstant hastighet eller konstant acceleration. Eleverna har möjlighet att utföra tre olika experiment som styrs via en webbsida eller fjärrkontroll och analysera utgången genom grafer som ritas upp. Lösningen testades med mycket gott resultat. Slutsatsen är att man på ett effektivt sätt kan förbättra fysikundervisningen med hjälp av praktiska experiment som eleverna själva kan utföra.

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    Newtonsandravagn
  • 156.
    Karginova, Nadezda
    et al.
    Petrozavodsk University, Petrozavodsk, Russia.
    Byttner, Stefan
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab).
    Svensson, Magnus
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Data-driven methods for classification of driving styles in buses2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    Fuel consumption and vehicle breakdown depend upon the driving style of the driver, for example, hard driving style leads to more wear and consequently more failures of vehicle components. Because of this, it is important to identify and classify the driver’s driving style in order to give the driver feedback through a driver assistance system. The driver would then be able to detect and learn to avoid a driving style that is not appropriate. The input data is provided by different sensors installed in the vehicle, where different drivers and driving routes have been measured. The data is subjectively classified into two different driving styles: normal and hard. Hard driving style can be characterized, for example, by rapid acceleration and braking. Since it is not trivial to build a model which is able to distinguish hard driving from normal, a data mining approach has been employed. In the paper, several classifiers are compared (including e.g. neural networks and decision trees) and a discussion is made on the advantages and disadvantages of the different methods. Copyright © 2012 SAE International.

  • 157.
    Karlsson, Jonathan
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Strand, Fredrik
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Hernandez-Diaz, Kevin
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Nilsson, Felix
    HMS Industrial Networks AB, Halmstad, Sweden.
    Visual Detection of Personal Protective Equipment and Safety Gear on Industry Workers2023Ingår i: Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods: February 22-24, 2023, in Lisbon, Portugal / [ed] Maria De Marsico; Gabriella Sanniti di Baja; Ana Fred, SciTePress, 2023, Vol. 1, s. 395-402Konferensbidrag (Refereegranskat)
    Abstract [en]

    Workplace injuries are common in today’s society due to a lack of adequately worn safety equipment. A system that only admits appropriately equipped personnel can be created to improve working conditions. The goal is thus to develop a system that will improve workers’ safety using a camera that will detect the usage of Personal Protective Equipment (PPE). To this end, we collected and labeled appropriate data from several public sources, which have been used to train and evaluate several models based on the popular YOLOv4 object detector. Our focus, driven by a collaborating industrial partner, is to implement our system into an entry control point where workers must present themselves to obtain access to a restricted area. Combined with facial identity recognition, the system would ensure that only authorized people wearing appropriate equipment are granted access. A novelty of this work is that we increase the number of classes to five objects (hardhat, safety vest, safety gloves, safety glasses, and hearing protection), whereas most existing works only focus on one or two classes, usually hardhats or vests. The AI model developed provides good detection accuracy at a distance of 3 and 5 meters in the collaborative environment where we aim at operating (mAP of 99/89%, respectively). The small size of some objects or the potential occlusion by body parts have been identified as potential factors that are detrimental to accuracy, which we have counteracted via data augmentation and cropping of the body before applying PPE detection. © 2023 by SCITEPRESS-Science and Technology Publications, Lda.

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  • 158.
    Karlsson, Stefan M.
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Lip-motion events analysis and lip segmentation using optical flow2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    We propose an algorithm for detecting the mouth events of opening and closing. Our method is translation and ro- tation invariant, works at very fast speeds, and does not re- quire segmented lips. The approach is based on a recently developed optical flow algorithm that handles the motion of linear structure in a stable and consistent way.Furthermore, we provide a semi-automatic tool for gen- erating groundtruth segmentation of video data, also based on the optical flow algorithm used for tracking keypoints at faster than 200 frames/second. We provide groundtruth for 50 sessions of speech of the XM2VTS database [16] avail- able for download, and the means to segment further ses- sions at a relatively small amount of user interaction.We use the generated groundtruth to test the proposed al- gorithm for detecting events, and show it to yield promising result. The semi-automatic tool will be a useful resource for researchers in need of groundtruth segmentation from video for the XM2VTS database and others.

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  • 159.
    Khandelwal, Siddhartha
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Gait Event Detection in the Real World2018Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Healthy gait requires a balance between various neuro-physiological systems and is considered an important indicator of a subject's physical and cognitive health status. As such, health-related applications would immensely benefit by performing long-term or continuous monitoring of subjects' gait in their natural environment and everyday lives. In contrast to stationary sensors such as motion capture systems and force plates, inertial sensors provide a good alternative for such gait analysis applications as they are miniature, cheap, mobile and can be easily integrated into wearable systems.

    This thesis focuses on improving overall gait analysis using inertial sensors by providing a methodology for detecting gait events in real-world settings. Although the experimental protocols for such analysis have been restricted to only highly-controlled lab-like indoor settings; this thesis presents a new gait database that consists of data from gait activities carried out in both, indoor and outdoor environments. The thesis shows how domain knowledge about gait could be formulated and utilized to develop methods that are robust and can tackle real-world challenges. It also shows how the proposed approach can be generalized to estimate gait events from multiple body locations. Another aspect of this thesis is to demonstrate that the traditionally used temporal error metrics are not enough for presenting the overall performance of gait event detection methods. The thesis introduces how non-parametric tests can be used to complement them and provide a better overview.

    The results of comparing the proposed methodology to state-of-the-art methods showed that the approach of incorporating domain knowledge into the time-frequency analysis of the signal was robust across different real-world scenarios and outperformed other methods, especially for the scenario involving variable gait speeds in outdoor settings. The methodology was also benchmarked on publicly available gait databases yielding good performance for estimating events from different body locations. To conclude, this thesis presents a road map for the development of gait analysis systems in real-world settings.

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  • 160.
    Khandelwal, Siddhartha
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    Wickström, Nicholas
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    Detecting Gait Events from Outdoor Accelerometer Data for Long-term and Continuous Monitoring Applications2014Ingår i: 13th International Symposium on 3D Analysis of Human Movement: 14–17 July, 2014, Lausanne, Switzerland, 2014, , s. 4s. 151-154Konferensbidrag (Refereegranskat)
    Abstract [en]

    Detecting gait events is the key to many gait analysis applications which would immensely benefit if the analysis could be carried out using wearable sensors in uncontrolled outdoor environments, enabling continuous monitoring and long-term analysis. This would allow exploring new frontiers in gait analysis by facilitating the availability of more data and empower individuals, especially patients, to avail the benefits of gait analysis in their everyday lives. Previous gait event detection algorithms impose many restrictions as they have been developed from data collected incontrolled, indoor environments. This paper proposes a robust algorithm that utilizes a priori knowledge of gait in conjunction with continuous wavelet transform analysis, to accurately identify heel strike and toe off, from noisy accelerometer signals collected during indoor and outdoor walking. The accuracy of the algorithm is evaluated by using footswitches that are considered as ground truth and the results are compared with another recently published algorithm.

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  • 161.
    Khandelwal, Siddhartha
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Wickström, Nicholas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Evaluation of the performance of accelerometer-based gait event detection algorithms in different real-world scenarios using the MAREA gait database2017Ingår i: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 51, s. 84-90Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Numerous gait event detection (GED) algorithms have been developed using accelerometers as they allow the possibility of long-term gait analysis in everyday life. However, almost all such existing algorithms have been developed and assessed using data collected in controlled indoor experiments with pre-defined paths and walking speeds. On the contrary, human gait is quite dynamic in the real-world, often involving varying gait speeds, changing surfaces and varying surface inclinations. Though portable wearable systems can be used to conduct experiments directly in the real-world, there is a lack of publicly available gait datasets or studies evaluating the performance of existing GED algorithms in various real-world settings.

    This paper presents a new gait database called MAREA (n=20 healthy subjects) that consists of walking and running in indoor and outdoor environments with accelerometers positioned on waist, wrist and both ankles. The study also evaluates the performance of six state-of-the-art accelerometer-based GED algorithms in different real-world scenarios, using the MAREA gait database. The results reveal that the performance of these algorithms is inconsistent and varies with changing environments and gait speeds. All algorithms demonstrated good performance for the scenario of steady walking in a controlled indoor environment with a combined median F1score of 0.98 for Heel-Strikes and 0.94 for Toe-Offs. However, they exhibited significantly decreased performance when evaluated in other lesser controlled scenarios such as walking and running in an outdoor street, with a combined median F1score of 0.82 for Heel-Strikes and 0.53 for Toe-Offs. Moreover, all GED algorithms displayed better performance for detecting Heel-Strikes as compared to Toe-Offs, when evaluated in different scenarios. © 2016 Elsevier B.V.

  • 162.
    Khandelwal, Siddhartha
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Wickström, Nicholas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Gait Event Detection in Real-World Environment for Long-Term Applications: Incorporating Domain Knowledge into Time-Frequency Analysis2016Ingår i: IEEE transactions on neural systems and rehabilitation engineering, ISSN 1534-4320, E-ISSN 1558-0210, Vol. 24, nr 12, s. 1363-1372Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Detecting gait events is the key to many gait analysis applications that would benefit from continuous monitoring or long-term analysis. Most gait event detection algorithms using wearable sensors that offer a potential for use in daily living have been developed from data collected in controlled indoor experiments. However, for real-word applications, it is essential that the analysis is carried out in humans’ natural environment; that involves different gait speeds, changing walking terrains, varying surface inclinations and regular turns among other factors. Existing domain knowledge in the form of principles or underlying fundamental gait relationships can be utilized to drive and support the data analysis in order to develop robust algorithms that can tackle real-world challenges in gait analysis. This paper presents a novel approach that exhibits how domain knowledge about human gait can be incorporated into time-frequency analysis to detect gait events from longterm accelerometer signals. The accuracy and robustness of the proposed algorithm are validated by experiments done in indoor and outdoor environments with approximately 93,600 gait events in total. The proposed algorithm exhibits consistently high performance scores across all datasets in both, indoor and outdoor environments. © Copyright 2016 IEEE

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  • 163.
    Khandelwal, Siddhartha
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Wickström, Nicholas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Novel methodology for estimating Initial Contact events from accelerometers positioned at different body locations2018Ingår i: Gait & Posture, ISSN 0966-6362, E-ISSN 1879-2219, Vol. 59, s. 278-285Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Identifying Initial Contact events (ICE) is essential in gait analysis as they segment the walking pattern into gait cycles and facilitate the computation of other gait parameters. As such, numerous algorithms have been developed to identify ICE by placing the accelerometer at a specific body location. Simultaneously, many researchers have studied the effects of device positioning for participant or patient compliance, which is an important factor to consider especially for long-term studies in real-life settings. With the adoption of accelerometery for long-term gait analysis in daily living, current and future applications will require robust algorithms that can either autonomously adapt to changes in sensor positioning or can detect ICE from multiple sensors locations.

    This study presents a novel methodology that is capable of estimating ICE from accelerometers placed at different body locations. The proposed methodology, called DK-TiFA, is based on utilizing domain knowledge about the fundamental spectral relationships present between the movement of different body parts during gait to drive the time-frequency analysis of the acceleration signal. In order to assess the performance, DK-TiFA is benchmarked on four large publicly available gait databases, consisting of a total of 613 subjects and 7 unique body locations, namely, ankle, thigh, center waist, side waist, chest, upper arm and wrist. The DK-TiFA methodology is demonstrated to achieve high accuracy and robustness for estimating ICE from data consisting of different accelerometer specifications, varying gait speeds and different environments. © 2017 Elsevier B.V.

  • 164.
    Kleyko, Denis
    et al.
    Luleå University of Technology, Luleå, Sweden.
    Hostettler, Roland
    Aalto University, Helsinki, Finland.
    Lyamin, Nikita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Birk, Wolfgang
    Luleå University of Technology, Luleå, Sweden.
    Wiklund, Urban
    Umea Univ, Dept Biomed Engn & Informat, Umea, Sweden..
    Osipov, Evgeny
    Luleå University of Technology, Luleå, Sweden.
    Vehicle Classification using Road Side Sensors and Feature-free Data Smashing Approach2016Ingår i: 2016 IEEE 19th International Conference on Intelligent Transportation Systems (ITSC), Piscataway: IEEE , 2016, s. 1988-1993, artikel-id 7795877Konferensbidrag (Refereegranskat)
    Abstract [en]

    The main contribution of this paper is a study of the applicability of data smashing - a recently proposed data mining method - for vehicle classification according to the "Nordic system for intelligent classification of vehicles" standard, using measurements of road surface vibrations and magnetic field disturbances caused by passing vehicles. The main advantage of the studied classification approach is that it, in contrast to the most of traditional machine learning algorithms, does not require the extraction of features from raw signals. The proposed classification approach was evaluated on a large dataset consisting of signals from 3074 vehicles. Hence, a good estimate of the actual classification rate was obtained. The performance was compared to the previously reported results on the same problem for logistic regression. Our results show the potential trade-off between classification accuracy and classification method's development efforts could be achieved.

  • 165. Kolf, Jan Niklas
    et al.
    Boutros, Fadi
    Elliesen, Jurek
    Theuerkauf, Markus
    Damer, Naser
    Alansarir, Mohamad
    Hay, Oussama Abdul
    Alansari, Sara
    Javed, Sajid
    Werghi, Naoufel
    Grm, Klemen
    Struc, Vojtech
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Hernandez Diaz, Karina
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Centrum för forskning om tillämpade intelligenta system (CAISR).
    George, Anjith
    Ecabert, Christian
    Shahreza, Hamed Omidvar
    Kotwal, Kshitij
    Marcel, Sebastien
    Medvedev, Ivan
    Bo, Jie
    Nunes, David
    Hassanpour, Ahmad
    Khatiwada, Pramod
    Toor, Ahsan Aftab
    Yang, Bian
    EFaR 2023: Efficient Face Recognition Competition2023Ingår i: Proc. IEEE/IAPR International Joint Conference on Biometrics (IJCB), 2023Konferensbidrag (Refereegranskat)
  • 166.
    Kollreider, Klaus
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Fronthaler, Hartwig
    Austrian Institute of Technology, Vienna, Austria .
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Real-Time Face Detection Using Illumination Invariant Features2007Ingår i: Image Analysis: Proceedings / [ed] Ersboll, B K, Pedersen, K S, Berlin: Springer, 2007, s. 41-50Konferensbidrag (Refereegranskat)
    Abstract [en]

    A robust object/face detection technique processing every frame in real-time (video-rate) is presented. A methodological novelty are the suggested quantized angle features (“quangles”), being designed for illumination invariance without the need for pre-processing, e.g. histogram equalization. This is achieved by using both the gradient direction and the double angle direction (the structure tensor angle), and by ignoring the magnitude of the gradient. Boosting techniques are applied in a quantized feature space. Separable filtering and the use of lookup tables favor the detection speed. Furthermore, the gradient may then be reused for other tasks as well. A side effect is that the training of effective cascaded classifiers is feasible in very short time, less than 1 hour for data sets of order 104. We present favorable results on face detection, for several public databases (e.g. 93% Detection Rate at 1×10− 6 False Positive Rate on the CMU-MIT frontal face test set).

  • 167.
    Krish, Ram P.
    et al.
    School of Electronic Engineering, Dublin City University, Ireland.
    Fierrez, Julian
    School of Engineering, Universidad Autonoma de Madrid, Spain.
    Ramos, Daniel
    School of Engineering, Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Improving Automated Latent Fingerprint Identification Using Extended Minutia Types2019Ingår i: Information Fusion, ISSN 1566-2535, E-ISSN 1872-6305, Vol. 50, s. 9-19Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Latent fingerprints are usually processed with Automated Fingerprint Identification Systems (AFIS) by law enforcement agencies to narrow down possible suspects from a criminal database. AFIS do not commonly use all discriminatory features available in fingerprints but typically use only some types of features automatically extracted by a feature extraction algorithm. In this work, we explore ways to improve rank identification accuracies of AFIS when only a partial latent fingerprint is available. Towards solving this challenge, we propose a method that exploits extended fingerprint features (unusual/rare minutiae) not commonly considered in AFIS. This new method can be combined with any existing minutiae-based matcher. We first compute a similarity score based on least squares between latent and tenprint minutiae points, with rare minutiae features as reference points. Then the similarity score of the reference minutiae-based matcher at hand is modified based on a fitting error from the least square similarity stage. We use a realistic forensic fingerprint casework database in our experiments which contains rare minutiae features obtained from Guardia Civil, the Spanish law enforcement agency. Experiments are conducted using three minutiae-based matchers as a reference, namely: NIST-Bozorth3, VeriFinger-SDK and MCC-SDK. We report significant improvements in the rank identification accuracies when these minutiae matchers are augmented with our proposed algorithm based on rare minutiae features. © 2018 Elsevier B.V.

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  • 168.
    Krish, Ram Prasad
    et al.
    Universidad Autonóma de Madrid, Madrid, Spain.
    Fierrez, Julian
    Universidad Autonóma de Madrid, Madrid, Spain.
    Ramos, Daniel
    Universidad Autonóma de Madrid, Madrid, Spain.
    Ortega-Garcia, Javier
    Universidad Autonóma de Madrid, Madrid, Spain.
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pre-registration of latent fingerprints based on orientation field2015Ingår i: IET Biometrics, ISSN 2047-4938, E-ISSN 2047-4946, Vol. 4, nr 2, s. 42-52Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In this study, the authors present a hierarchical algorithm to register a partial fingerprint against a full fingerprint using only the orientation fields. In the first level, they shortlist possible locations for registering the partial fingerprint in the full fingerprint using a normalised correlation measure, taking various rotations into account. As a second level, on those candidate locations, they calculate three other similarity measures. They then perform score fusion for all the estimated similarity scores to locate the final registration. By registering a partial fingerprint against a full fingerprint, they can reduce the search space of the minutiae set in the full fingerprint, thereby improving the result of partial fingerprint identification, particularly for poor quality latent fingerprints. They report the rank identification improvements of two minutiae-based automated fingerprint identification systems on the National Institute of Standards and Technology (NIST)-Special Database 27 database when they use the authors hierarchical registration as a pre-alignment. © The Institution of Engineering and Technology 2015.

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  • 169.
    Larsson, Bengt
    et al.
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Centrum för innovations-, entreprenörskaps- och lärandeforskning (CIEL).
    Mortin, Lizette
    Högskolan i Halmstad, Akademin för ekonomi, teknik och naturvetenskap, Centrum för innovations-, entreprenörskaps- och lärandeforskning (CIEL).
    Simmons, Christian
    Buller vid håltagning : Kan man reducera olägenheter vid ny- och ombyggnadsprojekt2007Rapport (Övrigt vetenskapligt)
  • 170.
    Larsson, Magnus
    Högskolan i Halmstad, Akademin för informationsteknologi.
    Pcapng Analysator: Utveckling av Pcapng analysator med inriktning på skräddarsydda nätverkspaket2024Självständigt arbete på grundnivå (högskoleexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
    Abstract [sv]

    I ett modernt industrisammanhang spelar kommunikation mellan inbyggda komponenter en viktig roll. Svetsmaskins företaget ESAB (Elektriska Svetsar AB) producerar och utvecklar svetsmaskiner med ett flertal olika inbyggda komponenter som kommunicerar sinsemellan för att konfigurera operationen för svetsning. Inom ramen för projektet på ESAB analyseras nätverkspaketen som skickas inom svetsmaskiner och som hämtas ut med hjälp av Wireshark. Nätverkspaketen används för systemkommunikations analys och hämtas ut i Pcapng-filformatet. Pcapng-filernagranskats manuellt med hjälp av Wireshark och deras skräddarsydda plugin, vilket kräver att varje paket inspekteras för att identifiera innehåll och potentiella felmeddelanden. Pcapng Analysatorn är ett program för att automatisera denna process och framhäva enbart de meddelanden och data som är av relevans för företaget. Denna rapport fokuserar på tekniker för manipulering och hantering av Pcapng-filer, samt metoder för extrahering av felmeddelanden från specialanpassade Pcapng-filer. Projektet representerar ett viktigt steg mot att effektivisera analysen av Pcapng-filer och att förse ESAB med en mer automatiserad och produktiv lösning för dataanalys inom sina verksamheter.

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  • 171.
    Lundström, Jens
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Situation Awareness in Colour Printing and Beyond2014Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Machine learning methods are increasingly being used to solve real-world problems in the society. Often, the complexity of the methods are well hidden for users. However, integrating machine learning methods in real-world applications is not a straightforward process and requires knowledge both about the methods and domain knowledge of the problem. Two such domains are colour print quality assessment and anomaly detection in smart homes, which are currently driven by manual monitoring of complex situations. The goal of the presented work is to develop methods, algorithms and tools to facilitate monitoring and understanding of the complex situations which arise in colour print quality assessment and anomaly detection for smart homes. The proposed approach builds on the use and adaption of supervised and unsupervised machine learning methods.

    Novel algorithms for computing objective measures of print quality in production are proposed in this work. Objective measures are also modelled to study how paper and press parameters influence print quality. Moreover, a study on how print quality is perceived by humans is presented and experiments aiming to understand how subjective assessments of print quality relate to objective measurements are explained. The obtained results show that the objective measures reflect important aspects of print quality, these measures are also modelled with reasonable accuracy using paper and press parameters. The models of objective  measures are shown to reveal relationships consistent to known print quality phenomena.

    In the second part of this thesis the application area of anomaly detection in smart homes is explored. A method for modelling human behaviour patterns is proposed. The model is used in order to detect deviating behaviour patterns using contextual information from both time and space. The proposed behaviour pattern model is tested using simulated data and is shown to be suitable given four types of scenarios.

    The thesis shows that parts of offset lithographic printing, which traditionally is a human-centered process, can be automated by the introduction of image processing and machine learning methods. Moreover, it is concluded that in order to facilitate robust and accurate anomaly detection in smart homes, a holistic approach which makes use of several contextual aspects is required.

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  • 172.
    Lundström, Jens
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Järpe, Eric
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Detecting and exploring deviating behaviour of people in their own homesManuskript (preprint) (Övrigt vetenskapligt)
    Abstract [en]

    A system for detecting deviating human behaviour in a smart home environment is the long-term goal of this work. It is believed that such systems will be very important in ambient assisted living services. Three types of deviations are considered in this work: deviation in activity intensity, deviation in time and deviation in space. Detection of deviations in activity intensity is formulated as the on-line quickest detection of a parameter shift in a sequence of independent Poisson random variables. Random forests trained in an unsupervised fashion are used to learn the spatial and temporal structure of data representing normal behaviour and are thereafter utilised to find deviations.The experimental investigations have shown that the Page and Shiryaev change-point detection methods are preferable in terms of expected delay of motivated alarm. Interestingly only a little is lost when the methods are specified with estimated intensity parameters rather than the true intensity values which are not available in a real situation. As to the spatial and temporal deviations, they can be revealed through analysis of a 2D map of high dimensional data. It was demonstrated that such a map is stable in terms of the number of clusters formed. We have shown that the data clusters can be understood/explored by finding the most important variables and by analysing the structure of the most representative tree.

  • 173.
    Lundström, Jens
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Järpe, Eric
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Detecting and exploring deviating behaviour of smart home residents2016Ingår i: Expert systems with applications, ISSN 0957-4174, E-ISSN 1873-6793, Vol. 55, s. 429-440Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A system for detecting deviating human behaviour in a smart home environment is the long-term goal of this work. Clearly, such systems will be very important in ambient assisted living services. A new approach to modelling human behaviour patterns is suggested in this paper. The approach reveals promising results in unsupervised modelling of human behaviour and detection of deviations by using such a model. Human behaviour/activity in a short time interval is represented in a novel fashion by responses of simple non-intrusive sensors. Deviating behaviour is revealed through data clustering and analysis of associations between clusters and data vectors representing adjacent time intervals (analysing transitions between clusters). To obtain clusters of human behaviour patterns, first, a random forest is trained without using beforehand defined teacher signals. Then information collected in the random forest data proximity matrix is mapped onto the 2D space and data clusters are revealed there by agglomerative clustering. Transitions between clusters are modelled by the third order Markov chain.

    Three types of deviations are considered: deviation in time, deviation in space and deviation in the transition between clusters of similar behaviour patterns.

    The proposed modelling approach does not make any assumptions about the position, type, and relationship of sensors but is nevertheless able to successfully create and use a model for deviation detection-this is claimed as a significant result in the area of expert and intelligent systems. Results show that spatial and temporal deviations can be revealed through analysis of a 2D map of high dimensional data. It is demonstrated that such a map is stable in terms of the number of clusters formed. We show that the data clusters can be understood/explored by finding the most important variables and by analysing the structure of the most representative tree. © 2016 Elsevier Ltd. All rights reserved.

  • 174.
    Lundström, Jens
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    Ourique de Morais, Wagner
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Cooney, Martin
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    A Holistic Smart Home Demonstrator for Anomaly Detection and Response2015Ingår i: 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), Piscataway, NJ: IEEE Press, 2015, s. 330-335Konferensbidrag (Refereegranskat)
    Abstract [en]

    Applying machine learning methods in scenarios involving smart homes is a complex task. The many possible variations of sensors, feature representations, machine learning algorithms, middle-ware architectures, reasoning/decision schemes, and interactive strategies make research and development tasks non-trivial to solve.In this paper, the use of a portable, flexible and holistic smart home demonstrator is proposed to facilitate iterative development and the acquisition of feedback when testing in regard to the above-mentioned issues. Specifically, the focus in this paper is on scenarios involving anomaly detection and response. First a model for anomaly detection is trained with simulated data representing a priori knowledge pertaining to a person living in an apartment. Then a reasoning mechanism uses the trained model to infer and plan a reaction to deviating activities. Reactions are carried out by a mobile interactive robot to investigate if a detected anomaly constitutes a true emergency. The implemented demonstrator was able to detect and respond properly in 18 of 20 trials featuring normal and deviating activity patterns, suggesting the feasibility of the proposed approach for such scenarios. © IEEE 2015

  • 175.
    Lundström, Jens
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Synnott, Jonathan
    Ulster University, Jordanstown, United Kingdom.
    Järpe, Eric
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Nugent, Christopher
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab). Ulster University, Jordanstown, United Kingdom.
    Smart Home Simulation using Avatar Control and Probabilistic Sampling2015Ingår i: 2015 IEEE International Conference on Pervasive Computing and Communication Workshops (PerCom Workshops), Piscataway, NJ: IEEE Press, 2015, s. 336-341Konferensbidrag (Refereegranskat)
    Abstract [en]

    Development, testing and validation of algorithms for smart home applications are often complex, expensive and tedious processes. Research on simulation of resident activity patterns in Smart Homes is an active research area and facilitates development of algorithms of smart home applications. However, the simulation of passive infrared (PIR) sensors is often used in a static fashion by generating equidistant events while an intended occupant is within sensor proximity. This paper suggests the combination of avatar-based control and probabilistic sampling in order to increase realism of the simulated data. The number of PIR events during a time interval is assumed to be Poisson distributed and this assumption is used in the simulation of Smart Home data. Results suggest that the proposed approach increase realism of simulated data, however results also indicate that improvements could be achieved using the geometric distribution as a model for the number of PIR events during a time interval. © IEEE 2015

  • 176.
    Lundström, Jens
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    Verikas, Antanas
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Laboratoriet för intelligenta system.
    System for Assessing, Exploring and Monitoring Offset Print Quality2011Ingår i: Recent Researches in Circuits, Systems, Communications & Computers: Proc. of 2nd European Conference of Communications (ECCOM'11), Athens: World Scientific and Engineering Academy and Society, 2011, s. 28-33Konferensbidrag (Refereegranskat)
    Abstract [en]

    Variations in offset print quality relate to numerous parameter of printing press and paper. To maintain constant quality of products, press operators need to assess, explore and monitor print quality. This paper presents a novel system for assessing and predicting values of print quality attributes, where the adopted, random forests (RF)-based, modeling approach also allows quantifying the influence of different parameters. In contrast to other print quality assessment systems, this system utilizes common print marks known as double grey-bars. A novel virtual sensor for assessing the mis-registration degree of printing plates using images of double grey-bars is presented. The inferred influence of paper and printing press parameters on print quality shows correlation with known print quality conditions.

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  • 177.
    Madagalam, Mallikarjun
    Högskolan i Halmstad, Akademin för informationsteknologi. Lund University.
    Pulse Energy Stabilization of a Femtosecond Laser Pulse Chain2016Självständigt arbete på avancerad nivå (magisterexamen), 10 poäng / 15 hpStudentuppsats (Examensarbete)
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  • 178.
    Malmberg, Donald
    et al.
    Mefos Met Res Plant, Lulea, Sweden .
    Björkvall, J.
    Mefos Met Res Plant, Lulea, Sweden .
    Malm, J.
    Mefos Met Res Plant, Lulea, Sweden .
    Bååth, Lars B.
    Högskolan i Halmstad, Sektionen för ekonomi och teknik (SET).
    Preliminary microwave measurements on liquid stags2005Ingår i: Ironmaking & steelmaking, ISSN 0301-9233, E-ISSN 1743-2812, Vol. 32, nr 1, s. 61-67Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Microwave technology has for decades been a tool for astronomers in their work to map and understand the complexities of the universe in terms of composition and extent but it is also used at laboratory scale by spectroscopists to examine the properties of atomic and molecular compounds. This paper discusses the use of microwave technology for the investigation of liquid slag structures. Preliminary results indicate that alteration of slag composition could be correlated to the measured microwave refractive index. Investigations have been performed on Al2 O3 -CaO-SiO2.

  • 179.
    Marcos, Mar
    et al.
    Universitat Jaume I, Castellón, Spain.
    Juarez, Jose M.University of Murcia, Murcia, Spain.Lenz, RichardFriedrich-Alexander-University of Erlangen-Nuremberg, Erlangen, Germany.Nalepa, Grzegorz J.Jagiellonian University and AGH University of Science and Technology, Kraków, Poland.Nowaczyk, SławomirHögskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).Peleg, MorUniversity of Haifa, Haifa, Israel.Stefanowski, JerzyPoznań University of Technology, Poznan, Poland.Stiglic, GregorUniversity of Maribor, Maribor, Slovenia.
    Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems2019Proceedings (redaktörskap) (Refereegranskat)
    Abstract [en]

    This book constitutes revised selected papers from the AIME 2019 workshops KR4HC/ProHealth 2019, the Workshop on Knowledge Representation for Health Care and Process-Oriented Information Systems in Health Care, and TEAAM 2019, the Workshop on Transparent, Explainable and Affective AI in Medical Systems.

    The volume contains 5 full papers from KR4HC/ProHealth, which were selected out of 13 submissions. For TEAAM 8 papers out of 10 submissions were accepted for publication. © 2019 Springer Nature Switzerland AG. Part of Springer Nature.

  • 180.
    Marinho, Marco A. M.
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Antreich, Felix
    Department of Telecommunications, Aeronautics Institute of Technology (ITA), São José dos Campos, Brazil.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Tufvesson, Fredrik
    Department of Electrical and Information Technology, Lund University, Lund, Sweden.
    Atif Yaqoob, Muhammad
    TerraNet AB, Lund, Sweden.
    Non-Line-of-Sight Based Radio Localization With Dual-Polarization Antenna Arrays2020Ingår i: WSA 2020: 24th International ITG Workshop on Smart Antennas, Berlin: VDE Verlag GmbH, 2020Konferensbidrag (Refereegranskat)
    Abstract [en]

    This work presents an approach for radio-based localization in non-line-of-sight (NLOS) environments by leveraging a dual-polarization antenna array. By estimating the polarization of the received signal, it is possible to estimate the angle of reflection of a NLOS signal. An estimate of the position of the transmitter concerning the receiver can be obtained based on a joint estimation of the reflection angle of several NLOS signals together with their respective directions of arrival (DOAs) and time differences of arrival (TDOAs). A set of numerical simulations is used to assess the performance of the proposed method. © VDE VERLAG GMBH. Berlin. Offenbach

  • 181.
    Marinho, Marco A. M.
    et al.
    University of Brasília (UnB), Brasília, Brazil & German Aerospace Center (DLR), Cologne, Germany.
    da Costa, João Paulo C. L.
    University of Brasília (UnB), Brasília, Brazil; llmenau University of Technology, Ilmenau, Germany & Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
    Antreich, Felix
    German Aerospace Center (DLR), Cologne, Germany.
    de Almeida, André L. F.
    Federal University of Ceará (UFC), Fortaleza, Brazil.
    Del Galdo, Giovanni
    llmenau University of Technology, Ilmenau, Germany & Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany.
    de Freitas, Edison Pignaton
    University of Brasília (UnB), Brasília, Brazil & Informatics Institute, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Array interpolation based on multivariate adaptive regression splines2016Ingår i: 2016 IEEE Sensor Array and Multichannel Signal Processing Workshop (SAM), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many important signal processing techniques such as Spatial Smoothing, Forward Backward Averaging and Root-MUSIC, rely on antenna arrays with specific and precise structures. Arrays with such ideal structures, such as a centro-hermitian structure, are often hard to build in practice. Array interpolation is used to enable the usage of these techniques with imperfect (not having a centro-hermitian structure) arrays. Most interpolation methods rely on methods based on least squares (LS) to map the output of a perfect virtual array based on the real array. In this work, the usage of Multivariate Adaptive Regression Splines (MARS) is proposed instead of the traditional LS to interpolate arrays with responses largely different from the ideal.

  • 182.
    Marinho, Marco A. M.
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi. University of Brasília (UnB), Department of Electrical Engineering (ENE), Brasília, Brazil.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Tufvesson, Fredrik
    Department of Electrical and Information Technology, Lund University, Lund, Sweden.
    Antreich, Felix
    Department of Teleinformatics Engineering - Federal University of Ceará (UFC), Fortaleza, Brazil.
    Da Costa, João Paulo C.L.
    University of Brasília (UnB), Department of Electrical Engineering (ENE), Brasília, Brazil.
    Performance Assessment for Distributed Broadband Radio Localization2018Ingår i: 2018 52nd Asilomar Conference on Signals, Systems, and Computers, Washington, DC: IEEE, 2018, s. 20-23Konferensbidrag (Refereegranskat)
    Abstract [en]

    Various emerging technologies, such as autonomous vehicles and fully autonomous flying, require precision positioning. This work presents a localization and tracking method based on joint direction of arrival (DOA), time delay, and range estimation using the SAGE algorithm. The proposed method does not rely on external sources of information such as global navigation satellite systems (GNSS). The method is opportunistic and does not require any location-based data exchange. A set of numerical simulations is presented to assess the performance of the proposed method.

  • 183.
    Marinho, Marco
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS). University of Brasília (UnB), Department of Electrical Engineering (ENE), Brasília, Brazil.
    Antreich, Felix
    Department of Teleinformatics Engineering Federal University of Ceará (UFC), Fortaleza, Brazil.
    da Costa, João Paulo C.L.
    University of Brasília (UnB), Department of Electrical Engineering (ENE), Brasília, Brazil.
    Caizzone, Steffano
    German Aerospace Center (DLR), Institute for Communications and Navigation, Wessling, Germany.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Pignaton de Freitas, Edison
    Federal University of Rio Grande do Sul (UFRGS), Informatics Institute, Porto Alegre, Brazil.
    Robust Nonlinear Array Interpolation for Direction of Arrival Estimation of Highly Correlated Signals2018Ingår i: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 144, s. 19-28Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Important signal processing techniques need that the response of the different elements of a sensor array has specific characteristics. For physical systems this often is not achievable as the array elements’ responses are affected by mutual coupling or other effects. In such cases, it is necessary to apply array interpolation to allow the application of ESPRIT, Forward Backward Averaging (FBA), and Spatial Smoothing (SPS). Array interpolation provides a model or transformation between the true and a desired array response. If the true response of the array becomes more distorted with respect to the desired one or the considered region of the field of view of the array increases, nonlinear approaches becomes necessary. This work presents two novel methods for sector discretization. An Unscented Transform (UT) based method and a principal component analysis (PCA) based method are discussed. Additionally, two novel nonlinear interpolation methods are developed based on the nonlinear regression schemes Multivariate Adaptive Regression Splines (MARS) and Generalized Regression Neural Networks (GRNNs). These schemes are extended and applied to the array interpolation problem. The performance of the proposed methods is examined using simulated and measured array responses of a physical system used for research on mutual coupling in antenna arrays. © 2017 The Author(s). Published by Elsevier B.V.

  • 184.
    Marques Marinho, Marco Antonio
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Array Processing Techniques for Direction of Arrival Estimation, Communications, and Localization in Vehicular and Wireless Sensor Networks2018Doktorsavhandling, monografi (Övrigt vetenskapligt)
    Abstract [en]

    Array signal processing in wireless communication has been a topic of interest in research for over three decades. In the fourth generation (4G) of the wireless communication systems, also known as Long Term Evolution (LTE), multi antenna systems have been adopted according to the Release 9 of the 3rd Generation Partnership Project (3GPP). For the fifth generation (5G) of the wireless communication systems, hundreds of antennas should be incorporated to the devices in a massive multi-user Multiple Input Multiple Output (MIMO) architecture. The presence of multiple antennas provides array gain, diversity gain, spatial gain, and interference reduction. Furthermore, arrays enable spatial filtering and parameter estimation, which can be used to help solve problems that could not previously be addressed from a signal processing perspective. The aim of this thesis is to bridge some gaps between signal processing theory and real world applications. Array processing techniques traditionally assume an ideal array. Therefore, in order to exploit such techniques, a robust set of methods for array interpolation are fundamental and are developed in this work. In this dissertation, novel methods for array interpolation are presented and their performance in real world scenarios is evaluated. Problems in the field of wireless sensor networks and vehicular networks are also addressed from an array signal processing perspective. Signal processing concepts are implemented in the context of a wireless sensor network. These concepts provide a level of synchronization sufficient for distributed multi antenna communication to be applied, resulting in improved lifetime and improved overall network behaviour. Array signal processing methods are proposed to solve the problem of radio based localization in vehicular network scenarios with applications in road safety and pedestrian protection.

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  • 185.
    Marques Marinho, Marco Antonio
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Gustafson, Per
    Gutec AB, Lomma, Sweden.
    Antreich, Felix
    Aeronautics Technology Institute, São José dos Campos, São Paulo, Brazil.
    Caizzone, Stefano
    German Aerospace Agency, Wessling, Germany.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Multi-Band Antenna Array Geometry Impact on Array Interpolation2021Konferensbidrag (Refereegranskat)
    Abstract [en]

    Multi-band or multi-frequency antennas have become essential for many GNSS applications [1]. These antennas allow a receiver to simultaneously receive from multiple bands such as L1, L2, L2C, E5A, L5, and so on, which is essential for ionosphere corrections, can help mitigating multipath induced biases, and improve overall system availability. Furthermore, they also allow for multiple GNSS to be used simultaneously, improving accuracy and robustness due to the larger number of satellites available.Another advancement that has recently attracted attention in the GNSS community is the usage of antenna arrays at the receiver [2], [3]. These arrays, which can assume multiple shapes and sizes, can be used to enhance system performance in multiple ways. Beamforming can be used to null out interferers or multipath components and improve gain over a designated direction of arrival. Some antenna array geometries can also enable a receiver to estimate its attitude while relying solely on received GNSS signals.While both multi-band antennas and antenna arrays offer attractive advantages for precise GNSS positioning, merging such systems on a single receiver can be challenging. Antenna arrays have their performance largely dictated by their geometries and the spacing between antenna elements [4]. This spacing is defined with respect to the frequency of the signal that is received at the antenna array. If the spacing is too large the receiver will suffer from inaccuracy introduced by ambiguities that will be present when trying to filter out undesired signals or when trying to estimate the direction of arrival of received signals. If the spacing is too small, the total array directivity will be lower, which will lead to more biased direction of arrival estimations or to beamformers with lobes that are too broad to filter out undesired signals.The relationship between frequency and geometry makes it impossible to create a multi-band antenna array that is optimal for every frequency received, as optimizing one frequency will inevitably lead to performance degradation in the remaining ones. To tackle this issue, a technique known as array interpolation can be employed [5]. Array interpolation consists of creating a mathematical transformation that projects the signal received at a real and imperfect array onto an ideal and abstract receiver. This allows arrays whose geometries are not optimal, and even heavily distorted with respect to an optimal geometry, to achieve high levels of performance, with improved direction of arrival estimation accuracy. A different array interpolation can be constructed for each individual frequency received at the array. Thus, array interpolation can be a valuable tool for allowing multi-band antenna arrays to achieve high performance over the entire range of frequencies they are designed to receive.This work studies the effects of optimizing antenna array geometries for a given frequency band while applying array interpolation over the array response for the remaining frequency bands. Furthermore, the possibility of choosing a geometry that is not optimal for any given array geometry but achieving an overall improved performance over the entire range of frequency bands to which the array is tuned is also studied. The performance of multiple array interpolation methods is verified, and the tradeoffs between performance and computational complexity is studied.[1] J. Li, H. Shi, H. Li, and A. Zhang, “Quad-band probe-fed stacked annular patch antenna for GNSS applications,” IEEE Antennas Wirel. Propag. Lett., vol. 13, pp. 372–375, 2014.[2] S. Caizzone, “Miniaturized E5a/E1 antenna array for robust GNSS navigation,” IEEE Antennas Wirel. Propag. Lett., vol. 16, pp. 485–488, 2016.[3] S. Caizzone, W. Elmarissi, M. A. M. Marinho, and F. Antreich, “Direction of arrival estimation performance for compact antenna arrays with adjustable size,” in IEEE MTT-S International Microwave Symposium Digest, 2017.[4] Y. T. Lo, S. W. Lee, and Q. H. Lee, “Optimization of directivity and signal-to-noise ratio of an arbitrary antenna array,” Proc. IEEE, vol. 54, no. 8, pp. 1033–1045, 1966.[5] M. A. M. Marinho, F. Antreich, S. Caizzone, J. P. C. L. da Costa, A. Vinel, and E. P. de Freitas, “Robust Nonlinear Array Interpolation for Direction of Arrival Estimation of Highly Correlated Signals,” Signal Processing, vol. 144, 2018. © 1995-2021, The Institute of Navigation, Inc.

  • 186.
    Marques Marinho, Marco Antonio
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Antreich, Felix
    Aeronautics Institute of Technology (ITA), Department of Telecommunications, São José dos Campos, São Paulo, Brazil.
    Gustafson, Per
    Gutec AB, Lomma, Sweden.
    GNSS Aided Non-Line-of-Sight Radio Localization via Dual Polarized Arrays2020Ingår i: WiP Proceedings of the International Conference on Localization and GNSS (ICL-GNSS 2020) / [ed] Aleksandr Ometov, Jari Nurmi, Elena Simona Lohan, Joaquín Torres-Sospedra and Heidi Kuusniemi, Aachen: Rheinisch-Westfaelische Technische Hochschule Aachen , 2020, Vol. 2626Konferensbidrag (Refereegranskat)
    Abstract [en]

    This work presents a radio based localization approach that is capable of accurately positioning radio emitters even when no direct line-of-sight signal is available. A dual polarized array is employed along with the space alternating generalized expectation maximization (SAGE) algorithm. To lighten the computational load and improve the accuracy of the proposed method, Global Navigation Satellite Systems (GNSS) positioning is used to initialize and limit the search area of SAGE. A set of numerical simulations is presented, highlighting the performance of the proposed method. © 2020 for this paper by its authors.

  • 187.
    Marques Marinho, Marco Antonio
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Pignaton de Freitas, Edison
    Federal University of Rio Grande do Sul (UFRGS), Informatics Institute, Porto Alegre, Brazil.
    Fernandez, Stephanie
    University of Brasilia (UnB), Department of Electrical Engineering (ENE), Brasilia, Brazil.
    Cooperative Localization for the Internet of Things2021Ingår i: 16. WONS 2021: Virtual Conference: 16th IEEE/IFIP Wireless On-demand Network systems and Services Conference (WONS), WONS 2021, Virtual Conference, March 9-11, 2021, International Federation for Information Processing, 2021, s. 95-99, artikel-id 9415583Konferensbidrag (Refereegranskat)
    Abstract [en]

    The internet of things (IoT) currently has a large range of applications, from wearable to smart cities. Many of these applications require that the nodes inside the networks know their relative or absolute position. To this end, multiple positioning methods can be applied, among such methods are Global Positioning Systems (GPS) or methods that employ time delay of arrival (TDOA). This work presents node localization methods that employ a dual polarization receiver on a single node, or a virtual array when multiple nodes are capable of coop- erating. The proposed approaches aim to minimize the economic cost associated with implementing localization methods, and can be done with simple hardware. The accuracy of the proposed methods is measured trough a set of numerical simulations. © IFIP

  • 188.
    Marques Marinho, Marco Antonio
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES).
    Tufvesson, F.
    Department of Electrical and Information Technology, Lund University.
    Antreich, F.
    Department of Telecommunications, Aeronautics Institute of Technology (ITA), São José dos Campos, Brazil.
    Costa, J.P.C.L.D.
    Department of Electrical Engineering (ENE), University of Brasília (UnB), Brasília, Brazil.
    Pignaton de Freitas, Edison
    Informatics Institute, Federal University of Rio Grande Do sul (UFRGS), Porto Alegre, Brazil.
    Spherical Wave Array Based Positioning for Vehicular Scenarios2020Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 8, s. 110073-110081, artikel-id 9112178Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Smart vehicles are emerging as a possible solution for multiple concerns in road traffic, such as mobility and safety. This work presents radio localization methods based on simultaneous direction of arrival (DOA), time-delay, and range estimation using the SAGE algorithm. The proposed methods do not rely on external sources of information, such as global navigation satellite systems (GNSS). The proposed methods take advantage of signals of opportunity and do not require the transmission of location-specific signals; therefore, they do not increase the network load. A set of simulations using synthetic and measured data is provided to validate the proposed methods, and the results show that it is possible to achieve accuracy down to decimeter and centimeter-level. © 2013 IEEE.

  • 189.
    Martinez-Diaz, M.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Siguenza, J. A.
    Universidad Autonoma de Madrid, Spain.
    Hill-climbing and brute-force attacks on biometric systems: A case study in Match-on-Card fingerprint verification2006Ingår i: Proceedings 2006: 40th Annual IEEE International Carnahan Conferences Security Technology, October 16-19, 2006, Lexington, Kentucky, Piscataway, N.J.: IEEE Press, 2006, s. 151-159Konferensbidrag (Refereegranskat)
    Abstract [en]

    In this paper, we study the robustness of state-of-theart automatic fingerprint verification systems against hill-climbing and brute-force attacks. We compare the performance of this type of attacks against two different minutiae-based systems, the NIST Fingerprint Image Software 2 (NFIS2) reference system and a Match-on-Card based system. In order to study their success rate, the attacks are analyzed and modified in each scenario. We focus on the influence of initial conditions in hill-climbing attacks, like the number of minutiae in the synthetically generated templates or the performance of each type of modification in the template. We demonstrate how slight modifications in the hill-climbing algorithm lead to very different success rates. © 2006 IEEE.

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  • 190.
    Mashad Nemati, Hassan
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Gholami Shahbandi, Saeed
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Åstrand, Björn
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Human Tracking in Occlusion based on Reappearance Event Estimation2016Ingår i: ICINCO 2016: 13th International Conference on Informatics in Control, Automation and Robotics: Proceedings, Volume 2 / [ed] Oleg Gusikhin, Dimitri Peaucelle & Kurosh Madani, SciTePress, 2016, Vol. 2, s. 505-512Konferensbidrag (Refereegranskat)
    Abstract [en]

    Relying on the commonsense knowledge that the trajectory of any physical entity in the spatio-temporal domain is continuous, we propose a heuristic data association technique. The technique is used in conjunction with an Extended Kalman Filter (EKF) for human tracking under occlusion. Our method is capable of tracking moving objects, maintain their state hypothesis even in the period of occlusion, and associate the target reappeared from occlusion with the existing hypothesis. The technique relies on the estimation of the reappearance event both in time and location, accompanied with an alert signal that would enable more intelligent behavior (e.g. in path planning). We implemented the proposed method, and evaluated its performance with real-world data. The result validates the expected capabilities, even in case of tracking multiple humans simultaneously.

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  • 191.
    Menezes, Maria Luiza Recena
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Methodology for Subject Authentification and Identification through EEG signal: equipment's and positioning artifacts2018Ingår i: A2IC 2018: Artificial Intelligence International Conference: Book of Abstract, 2018, s. 37-37Konferensbidrag (Refereegranskat)
  • 192.
    Menezes, Maria Luiza Recena
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Pavel, Misha
    Northeastern University, Boston, USA.
    Jimison, Holly
    Northeastern University, Boston, USA.
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Affective Ambient Intelligence: from Domotics to Ambient Intelligence2018Ingår i: A2IC 2018: Artificial Intelligence International Conference: Book of Abstract, 2018, s. 25-25Konferensbidrag (Refereegranskat)
  • 193.
    Menezes, Maria Luiza Recena
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS).
    Samara, A.
    School of Computing and Mathematics, Ulster University Belfast, Belfast, United Kingdom.
    Galway, L.
    School of Computing and Mathematics, Ulster University Belfast, Belfast, United Kingdom.
    Pinheiro Sant'Anna, Anita
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Wang, H.
    School of Computing and Mathematics, Ulster University Belfast, Belfast, United Kingdom.
    Bond, R.
    School of Computing and Mathematics, Ulster University Belfast, Belfast, United Kingdom.
    Towards emotion recognition for virtual environments: an evaluation of eeg features on benchmark dataset2017Ingår i: Personal and Ubiquitous Computing, ISSN 1617-4909, E-ISSN 1617-4917, Vol. 21, nr 6, s. 1003-1013Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    One of the challenges in virtual environments is the difficulty users have in interacting with these increasingly complex systems. Ultimately, endowing machines with the ability to perceive users emotions will enable a more intuitive and reliable interaction. Consequently, using the electroencephalogram as a bio-signal sensor, the affective state of a user can be modelled and subsequently utilised in order to achieve a system that can recognise and react to the user’s emotions. This paper investigates features extracted from electroencephalogram signals for the purpose of affective state modelling based on Russell’s Circumplex Model. Investigations are presented that aim to provide the foundation for future work in modelling user affect to enhance interaction experience in virtual environments. The DEAP dataset was used within this work, along with a Support Vector Machine and Random Forest, which yielded reasonable classification accuracies for Valence and Arousal using feature vectors based on statistical measurements and band power from the and waves and High Order Crossing of the EEG signal. © 2017, The Author(s).

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  • 194.
    Midtiby, Henrik Skov
    et al.
    The Maersk Mc-Kinney Moller Institute, University of Southern Denmark, Odense, Denmark.
    Åstrand, Björn
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Jørgensen, Ole
    Operations Management, Aarhus University, Tjele, Denmark.
    Jørgensen, Rasmus Nyholm
    Signal Processing, Aarhus University, Aarhus, Denmark.
    Upper limit for context-based crop classification in robotic weeding applications2016Ingår i: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 146, s. 183-192Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Knowledge of the precise position of crop plants is a prerequisite for effective mechanical weed control in robotic weeding application such as in crops like sugar beets which are sensitive to mechanical stress. Visual detection and recognition of crop plants based on their shapes has been described many times in the literature. In this paper the potential of using knowledge about the crop seed pattern is investigated based on simulated output from a perception system. The reliability of position–based crop plant detection is shown to depend on the weed density (ρ, measured in weed plants per square metre) and the crop plant pattern position uncertainty (σx and σy, measured in metres along and perpendicular to the crop row, respectively). The recognition reliability can be described with the positive predictive value (PPV), which is limited by the seeding pattern uncertainty and the weed density according to the inequality: PPV ≤ (1 + 2πρσxσy)−1. This result matches computer simulations of two novel methods for position–based crop recognition as well as earlier reported field–based trials. © 2016 IAgrE

  • 195.
    Mikaelyan, Anna
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Alonso-Fernandez, Fernando
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Periocular Recognition by Detection of Local Symmetry Patterns2014Ingår i: Proceedings: Tenth International Conference on Signal-Image Technology and Internet-Based System: 23–27 November 2014: Marrakech, Morocco / [ed] Kokou Yetongnon, Albert Dipanda & Richard Chbeir, Los Alamitos, CA: IEEE Computer Society, 2014, s. 584-591Konferensbidrag (Refereegranskat)
    Abstract [en]

    We present a new system for biometric recognition using periocular images. The feature extraction method employed describes neighborhoods around keypoints by projection onto harmonic functions which estimates the presence of a series of various symmetric curve families around such keypoints. The iso-curves of such functions are highly symmetric w.r.t. the keypoints and the estimated coefficients have well defined geometric interpretations. The descriptors used are referred to as Symmetry Assessment by Feature Expansion (SAFE). Extraction is done across a set of discrete points of the image, uniformly distributed in a rectangular-shaped grid positioned in the eye center. Experiments are done with two databases of iris data, one acquired with a close-up iris camera, and another in visible light with a webcam. The two databases have been annotated manually, meaning that the radius and center of the pupil and sclera circles are available, which are used as input for the experiments. Results show that this new system has a performance comparable with other periocular recognition approaches. We particularly carry out comparative experiments with another periocular system based on Gabor features extracted from the same set of grid points, with the fusion of the two systems resulting in an improved performance. We also evaluate an iris texture matcher, providing fusion results with the periocular systems as well.

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  • 196.
    Mikaelyan, Anna
    et al.
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Sektionen för Informationsvetenskap, Data– och Elektroteknik (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Frequency and ridge estimation using structure tensor2013Ingår i: Proceedings of Biometric Technologies in Forensic Science: Nijmegen, 14–15 October 2013, Nijmegen: Radboud University Nijmegen , 2013, s. 58-59Konferensbidrag (Refereegranskat)
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    mikaelyan2013ridge
  • 197.
    Mikaelyan, Anna
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    SAFE features for matching fingermarks by neighbourhoods of single minutiae2014Ingår i: 2014 14th International Symposium on Communications and Information Technologies (ISCIT), Piscataway, N.J.: IEEE Press, 2014, s. 181-185, artikel-id 7011896Konferensbidrag (Refereegranskat)
    Abstract [en]

    Symmetry Assessment by Finite Expansion (SAFE) is a novel description of image information by means of Generalized Structure Tensor. It represents orientation data in neighbourhood of key points projected onto the space of harmonic functions creating a geometrically interpretable feature of low dimension. The proposed feature has built in quality metrics reflecting accuracy of the extracted feature and ultimately the quality of the key point. The feature vector is orientation invariant in that it is orientation steerable with low computational cost. We provide experiments on minutia key points of forensic fingerprints to demonstrate its usefulness. Matching is performed based on minutia in regions with high orientation variance, e.g. in proximity of core points. Performance of single matching minutia equals to 20% EER and Rank-20 CMC 69% on the only publicly available annotated forensic fingerprint SD27 database.

    Further, we complement SAFE descriptors of orientation maps with SAFE descriptors of frequency features in a similar manner. In case of combined features the performance is improved further to 19% EER and 74% Rank-20 CMC. © 2014 IEEE.

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    mikaelyan14min
  • 198.
    Mikaelyan, Anna
    et al.
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Bigun, Josef
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR Centrum för tillämpade intelligenta system (IS-lab).
    Symmetry Assessment by Finite Expansion: application to forensic fingerprints2014Ingår i: 2014 International Conference of the Biometrics Special Interest Group (BIOSIG) / [ed] Arslan Brömme & Christoph Busch, Bonn: Gesellschaft für Informatik, 2014, s. 87-98Konferensbidrag (Refereegranskat)
    Abstract [en]

    Common image features have too poor information for identification of forensic images of fingerprints, where only a small area of the finger is imaged and hence a small amount of key points are available. Noise, nonlinear deformation, and unknown rotation are additional issues that complicate identification of forensic fingerprints. We propose a feature extraction method which describes image information around key points: Symmetry Assessment by Finite Expansion (SAFE). The feature set has built-in quality estimates as well as a rotation invariance property. The theory is developed for continuous space, allowing compensation for features directly in the feature space when images undergo such rotation without actually rotating them. Experiments supporting that use of these features improves identification of forensic fingerprint images of the public NIST SD27 database are presented. Performance of matching orientation information in a neighborhood of core points has an EER of 24% with these features alone, without using minutiae constellations, in contrast to 36% when using minutiae alone. Rank-20 CMC is 58%, which is lower than 67% when using notably more manually collected minutiae information.

  • 199.
    Minelga, Jonas
    et al.
    Kaunas University of Technology, Kaunas, Lithuania.
    Gelzinis, Adas
    Kaunas University of Technology, Kaunas, Lithuania.
    Vaiciukynas, Evaldas
    Kaunas University of Technology, Kaunas, Lithuania.
    Verikas, Antanas
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligenta system (IS-lab). Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Padervinskis, Evaldas
    Department of Otolaryngology, Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Uloza, Virgilijus
    Department of Otolaryngology, Lithuanian University of Health Sciences, Kaunas, Lithuania.
    Comparing Throat and Acoustic Microphones for Laryngeal Pathology Detection from Human Voice2014Ingår i: Electrical and Control Technologies: Proceedings of the 9th International Conference on Electrical and Control Technologies ECT-2014 / [ed] A. Navickas (general editor), A. Sauhats, A. Virbalis, M. Ažubalis, V. Galvanauskas, K. Brazauskas & A. Jonaitis, Kaunas: Kaunas University of Technology , 2014, s. 50-53Konferensbidrag (Refereegranskat)
    Abstract [en]

    The aim of this study was to compare acoustic and throat microphones in the voice pathology detection task. Recordings of sustained phonation /a/ were used in the study. Each recording was characterized by a rather large set of diverse features, 1051 features in total. Classification into two classes, namely normal and pathological, was performed using random forest committees. Models trained using data obtained from the throat microphone provided lower classification accuracy. This is probably due to a narrower frequency range of the throat microphone leading to loss of important information. © Kaunas University of Technology, 2014.

  • 200.
    Molchanov, Pavlo
    et al.
    Tampere University of Technology, Tampere, Finland.
    Vinel, Alexey
    Högskolan i Halmstad, Akademin för informationsteknologi, Halmstad Embedded and Intelligent Systems Research (EIS), Centrum för forskning om inbyggda system (CERES). Tampere University of Technology, Tampere, Finland.
    Astola, Jaakko
    Tampere University of Technology, Tampere, Finland.
    Egiazarian, Karen
    Tampere University of Technology, Tampere, Finland.
    Radar frequency band invariant pedestrian classification2013Ingår i: International Radar Symposium, IRS 2013: Proceedings, Volume II / [ed] Hermann Rohling, Göttingen, Germany: Cuvillier Verlag, 2013, s. 740-745Konferensbidrag (Refereegranskat)
    Abstract [en]

    The problem of pedestrian classification by radars with different operating bands is considered. The proposed solutions are based on two observations of relation between Doppler spectrums collected within different frequency bands. According to the first observation the Doppler spectrum obtained from the radars with lower operating frequency is an approximate scaled version of the Doppler spectrum obtained within radar with higher operating frequency. According to the second observation the Doppler spectrum of lower operating frequency is similar to the Doppler spectrum of higher operating frequency at specific aspect angle. Two new approaches are proposed for pedestrian classification based on the observations. The first proposed approach deals with new features called local binary mask. The second approach is based on higher order spectral invariants estimated from the Doppler spectrum. The approaches are tested on real 24 GHz radar measurements and simulated 77 GHz radar measurements and show the robustness to operating frequency of the radar. © 2013 German Inst of Navigation.

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