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  • 51.
    ALRimawi, Mohammed
    Halmstad University, School of Information Technology.
    Doppler Wheel for Emulation of Automotive Radar Target2019Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Automotive radar is an emerging field of research and development. Technological ‎advancements in this field will improve safety for vehicles, pedestrians, and ‎bicyclists, and enable the development of autonomous vehicles. Usage of the ‎Automotive radar is expanding ‎in car and road areas to reduce collisions and ‎accident. Automotive radar ‎developers face a problem to test their radar sensor in ‎the street since there are a lot of interferences ‎signals, noise and unpredicted ‎situations. This thesis provides a part of the solution for this problem by designing a ‎device can demonstrate a different speeds value. This device will help the developer ‎to test their radar sensor inside an anechoic chamber room that provides accurate ‎control of the environmental conditions. This report shows how to ‎build the ‎measuring setup device, step by step to demonstrate the people and vehicle’s speed ‎‎in the street by a Doppler emulator using the wheel for millimetre FWMC radar. ‎Linear speed system needs a large space for testing, but using the rotational wheel ‎allow the developer to test the radar sensor in a small area. It begins with the wheel ‎design specifications and the relation between the ‎rotational speed (RPM) of the ‎wheel and the Doppler frequency. The Doppler ‎frequency is changed by varying the ‎speed of the wheel. Control and power circuit ‎was carefully designed to control the ‎wheel speed accurately. All the measuring ‎setup device parts were assembled in one ‎box. Also, signal processing was done by ‎MATLAB to measure the Doppler frequency ‎using millimetre FMCW radar sensor. ‎The measuring setup device was tested in the ‎anechoic chamber room for different speeds. the ‎manual and automatic tests show ‎good results to measure the different wheel speeds ‎with high accuracy.‎

  • 52. Andersson, Emil
    et al.
    Schedin, Niklas
    Räkning av Personer i Rörelse med Bildtolkning2016Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    In today's society companies are dependent on market researches in order to continue to grow. A typical research could be the flow of people in department stores. This project is targeted to develop an image processing algorithm that can count the number of people that passes by a camera. The system comprises of two counters, one for people that enters and one for those who exits. To solve this problem the project has been divided in to two parts, education and development. The reason for having an education part, is to get some knowledge about image processing since the project members do not have any prior knowledge. The development part is when the final algorithm is being developed from the knowledge that has been aquired during the education part. The final result shows that the algorithm is reliable at low loads, but when it is strained by more people then the counter starts to deviate from the actual values.

  • 53.
    Andreasson, Henrik
    et al.
    Örebro University, Örebro, Sweden.
    Bouguerra, Abdelbaki
    Örebro University, Örebro, Sweden.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Gold-fish SLAM: An application of SLAM to localize AGVs2014In: Field and Service Robotics: Results of the 8th International Conference / [ed] Kazuya Yoshida & Satoshi Tadokoro, Heidelberg: Springer, 2014, p. 585-598Conference paper (Refereed)
    Abstract [en]

    The main focus of this paper is to present a case study of a SLAM solution for Automated Guided Vehicles (AGVs) operating in real-world industrial environments. The studied solution, called Gold-fish SLAM, was implemented to provide localization estimates in dynamic industrial environments, where there are static landmarks that are only rarely perceived by the AGVs. The main idea of Gold-fish SLAM is to consider the goods that enter and leave the environment as temporary landmarks that can be used in combination with the rarely seen static landmarks to compute online estimates of AGV poses. The solution is tested and verified in a factory of paper using an eight ton diesel-truck retrofitted with an AGV control system running at speeds up to 3m/s. The paper includes also a general discussion on how SLAM can be used in industrial applications with AGVs. © Springer-Verlag Berlin Heidelberg 2014.

  • 54.
    Belyaev, Evgeny
    et al.
    Department of Signal Processing, Tampere University of Technology, Tampere, Finland.
    Molchanov, Pavlo
    Department of Signal Processing, Tampere University of Technology, Tampere, Finland.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES). Department of Electronics and Communication Engineering, Tampere University of Technology, Tampere, Finland.
    Koucheryavy, Yevgeni
    Department of Electronics and Communication Engineering, Tampere University of Technology, Tampere, Finland.
    The Use of Automotive Radars in Video-Based Overtaking Assistance Applications2013In: IEEE transactions on intelligent transportation systems (Print), ISSN 1524-9050, E-ISSN 1558-0016, Vol. 14, no 3, p. 1035-1042, article id 649464Article in journal (Refereed)
    Abstract [en]

    Overtaking on rural roads may cause severe accidents when oncoming traffic is detected by a driver too late, or its speed is underestimated. Recently proposed cooperative overtaking assistance systems are based on real-time video transmission, where a video stream captured with a camera installed at the windshield of a vehicle is compressed, broadcast through the wireless channel, and displayed to the drivers of vehicles driving behind. In such a system, it is of ultimate importance to deliver video information about the opposite lane with low end-to-end latency and good visual quality. In this paper, we propose reallocating the wireless channel resources in favor of the part of the captured video frame containing the image of the oncoming vehicle. To achieve this goal, we apply automotive radar for oncoming vehicle detection, and we use the image of this vehicle as a region-of-interest (ROI) for the video rate control. We present the theoretical framework, which describes the basics of such an approach and can serve as a useful guideline for the future practical implementation of the overtaking assistance systems. The benefits of our proposal are demonstrated in relation to the practical scenario of H.264/Advance Video Coding (AVC), IEEE 802.11p/Wireless Access for Vehicular Environments (WAVE) intervehicle communication standards, and currently used automotive radars.

  • 55.
    Bengtsson, Ola
    Chalmers tekniska högskola Göteborg.
    Robust self-localization of mobile robots in dynamic environments using scan matching algorithms2006Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    The most fundamental task for any mobile robot is to perform self-localization in the world in which it is currently active, i.e. determine its position relative its world. Encoders that count wheel rotations are often used, which can be turned into relative position estimates by mean of integration. This process is commonly referred to as dead reckoning. Unfortunately, the errors in such position estimates grow over time due to the underlying measurements errors, which means that the errors in the dead reckoning estimates must be regularly corrected by absolute postion estimates provided by other sensors. The goal of this thesis is to evaluate the possibilities of using so called scan mathing algorithms for robust position estimation of a mobile robot, especially in environments that change over time. A scan is a set o range measurements of the environment provided by e.g. a laser scanner. By comparing a scan taken at the actual poition of the robot with a scan previously taken and stored in a map of the environment, an estimate of the absolute position of the robot can be obtained. It is important that scan matching algorithms are robust against changes in the environments, are robust against different types of environments and can judge their own results.

    The main contributions of the thesis are threefold. First, two new sector-based scan matching algorithms are presented that are based on two existing scan-matching algorithms known as the Cox's and IDC algorithm. The sector-based variants, Cox-S and IDC-S, increase the performance of the existing algorithms, especially in environments containing severe changes. Second, two new methods are presented for estimating the uncertainty of the IDC algorithm. These methods improve the self-judgment of the IDC and IDC-S significantly, as the existing method for estimating the uncertainty was not reliable. Third, the new sector-based scan matching algorithms are evaluated and compared to the existing algorithms on the basis of simulations and real world experiments made with two different mobile robots. The experiments focus on the performance of the algorithms in hanging environments, and on their performance as part of a complete loalization system, i.e. fusing the outcome with dead reckoning. The experiments show a clear advantage of using sector-based scan matching algorithms in terms of increased robustness against changed environments. The experiments show that use especially of a combination of the two sector based algorithms Cox-S and IDC-S, while also using the new method for estimating the uncertainty of the IDC-S, achieves significantly better performance in changing environments compared to the existing algorithms.

  • 56.
    Bengtsson, Ola
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Baerveldt, Albert-Jan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Localization in changing environments - Estimation of a covariance matrix for the IDC algorithm2001In: Proceedings 2001 IEEE/RSJ International Conference on Intelligent Robots and Systems. Expanding the Societal Role of Robotics in the the Next Millennium (Cat. No.01CH37180): Volume 4 of 4, Piscataway, N.J.: IEEE, 2001, p. 1931-1937Conference paper (Refereed)
    Abstract [en]

    Previously we have presented a new scan-matching algorithm, based on the IDC - Iterative Dual Correspondence- algorithm, which showed a good localization performance even in the case of severe changes in the environment. The Problem of the IDC-algorithm is that there is no good way to estimate the covariance matrix of the position estimate, which prohibits an effective fusion with other position estimates from other sensors, e.g by means of the Kalman filter. In this paper we present a new way to estimate the covariance matrix, by estimating the Hessian matrix of the error function that is minimized by the IDC scan-matching algorithm. Simulation results show that the estimated covariance matrix correspond well to the real one.

  • 57.
    Bigun, Josef
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Karlsson, Stefan M.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Histogram of directions by the structure tensor2011In: Proceedings of the 4th International Symposium on Applied Sciences in Biomedical and Communication Technologies, New York, NY: Association for Computing Machinery (ACM), 2011Conference paper (Refereed)
    Abstract [en]

    Many low-level features, as well as varying methods of extraction and interpretation rely on directionality analysis (for example the Hough transform, Gabor filters, SIFT descriptors and the structure tensor). The theory of the gradient based structure tensor (a.k.a. the second moment matrix) is a very well suited theoretical platform in which to analyze and explain the similarities and connections (indeed often equivalence) of supposedly different methods and features that deal with image directionality. Of special interest to this study is the SIFT descriptors (histogram of oriented gradients, HOGs). Our analysis of interrelationships of prominent directionality analysis tools offers the possibility of computation of HOGs without binning, in an algorithm of comparative time complexity.

  • 58.
    Bigun, Josef
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Mikaelyan, Anna
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Frequency map by Structure Tensor in Logarithmic Scale Space and Forensic Fingerprints2016In: PROCEEDINGS OF 29TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS, (CVPRW 2016), Piscataway, NJ: IEEE, 2016, p. 204-213, article id 7789522Conference paper (Refereed)
    Abstract [en]

    Increasingly, absolute frequency and orientation maps are needed, e.g. for forensics. We introduce a non-linear scale space via the logarithm of trace of the Structure Tensor. Therein, frequency estimation becomes an orientation estimation problem. We show that this offers significant advantages, including construction of efficient isotropic estimations of dense maps of frequency. In fingerprints, both maps are shown to improve each other in an enhancement scheme via Gabor filtering. We suggest a novel continuous ridge counting method, relying only on dense absolute frequency and orientation maps, without ridge detection, thinning, etc. Furthermore, we present new evidence that frequency maps are useful attributes of minutiae. We verify that the suggested method compares favorably with state of the art using forensic fingerprints as test bed, and test images where the ground truth is known. In evaluations, we use public data sets and published methods only.

  • 59.
    Bouguelia, Mohamed-Rafik
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Payberah, Amir H.
    Swedish Institute of Computer Science, Stockholm, Sweden.
    An adaptive algorithm for anomaly and novelty detection in evolving data streams2018In: Data mining and knowledge discovery, ISSN 1384-5810, E-ISSN 1573-756X, Vol. 32, no 6, p. 1597-1633Article in journal (Refereed)
    Abstract [en]

    In the era of big data, considerable research focus is being put on designing efficient algorithms capable of learning and extracting high-level knowledge from ubiquitous data streams in an online fashion. While, most existing algorithms assume that data samples are drawn from a stationary distribution, several complex environments deal with data streams that are subject to change over time. Taking this aspect into consideration is an important step towards building truly aware and intelligent systems. In this paper, we propose GNG-A, an adaptive method for incremental unsupervised learning from evolving data streams experiencing various types of change. The proposed method maintains a continuously updated network (graph) of neurons by extending the Growing Neural Gas algorithm with three complementary mechanisms, allowing it to closely track both gradual and sudden changes in the data distribution. First, an adaptation mechanism handles local changes where the distribution is only non-stationary in some regions of the feature space. Second, an adaptive forgetting mechanism identifies and removes neurons that become irrelevant due to the evolving nature of the stream. Finally, a probabilistic evolution mechanism creates new neurons when there is a need to represent data in new regions of the feature space. The proposed method is demonstrated for anomaly and novelty detection in non-stationary environments. Results show that the method handles different data distributions and efficiently reacts to various types of change. © 2018 The Author(s)

  • 60.
    Bouguelia, Mohamed-Rafik
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Santosh, K. C.
    The University of South Dakota, Vermillion, South Dakota, USA.
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Agreeing to disagree: active learning with noisy labels without crowdsourcing2018In: International Journal of Machine Learning and Cybernetics, ISSN 1868-8071, E-ISSN 1868-808X, Vol. 9, no 8, p. 1307-1319Article in journal (Refereed)
    Abstract [en]

    We propose a new active learning method for classification, which handles label noise without relying on multiple oracles (i.e., crowdsourcing). We propose a strategy that selects (for labeling) instances with a high influence on the learned model. An instance x is said to have a high influence on the model h, if training h on x (with label y = h(x)) would result in a model that greatly disagrees with h on labeling other instances. Then, we propose another strategy that selects (for labeling) instances that are highly influenced by changes in the learned model. An instance x is said to be highly influenced, if training h with a set of instances would result in a committee of models that agree on a common label for x but disagree with h(x). We compare the two strategies and we show, on different publicly available datasets, that selecting instances according to the first strategy while eliminating noisy labels according to the second strategy, greatly improves the accuracy compared to several benchmarking methods, even when a significant amount of instances are mislabeled. © Springer-Verlag Berlin Heidelberg 2017

  • 61.
    Bouguelia, Mohamed-Rafik
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Pashami, Sepideh
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Multi-Task Representation Learning2017In: 30th Annual Workshop ofthe Swedish Artificial Intelligence Society SAIS 2017: May 15–16, 2017, Karlskrona, Sweden / [ed] Niklas Lavesson, Linköping: Linköping University Electronic Press, 2017, p. 53-59Conference paper (Refereed)
    Abstract [en]

    The majority of existing machine learning algorithms assume that training examples are already represented with sufficiently good features, in practice ones that are designed manually. This traditional way of preprocessing the data is not only tedious and time consuming, but also not sufficient to capture all the different aspects of the available information. With big data phenomenon, this issue is only going to grow, as the data is rarely collected and analyzed with a specific purpose in mind, and more often re-used for solving different problems. Moreover, the expert knowledge about the problem which allows them to come up with good representations does not necessarily generalize to other tasks. Therefore, much focus has been put on designing methods that can automatically learn features or representations of the data instead of learning from handcrafted features. However, a lot of this work used ad hoc methods and the theoretical understanding in this area is lacking.

  • 62.
    Byttner, Stefan
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Prytz, Rune
    Volvo Group Trucks Technology, Gothenburg, Sweden.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    A field test with self-organized modeling for knowledge discovery in a fleet of city buses2013In: 2013 IEEE International Conference on Mechatronics and Automation (ICMA 2013) / [ed] Shuxiang Guo, Piscataway, NJ: IEEE Press, 2013, p. 896-901, article id 6618034Conference paper (Refereed)
    Abstract [en]

    Fleets of commercial vehicles represent an excellent real life setting for ubiquitous knowledge discovery. There are many electronic control units onboard a modern bus or truck, with hundreds of signals being transmitted between them on the controller area network. The growing complexity of the vehicles has lead to a significant desire to have systems for fault detection, remote diagnostics and maintenance prediction. This paper aims to show that it is possible to discover useful diagnostic knowledge by a self-organized algorithm in the scenario of a fleet of city buses. The approach is demonstrated as a process consisting of two parts; Unsupervised modeling (where interesting features are discovered) and Guided search (where the previously found features are coupled to additional information sources). The modeling part searches for simple linear models in a group of vehicles, where interesting features are selected based on both non-randomness in relations and variability in the group. It is shown in an eight months long data collection study that this approach was able to discover features related to broken wheelspeed sensors. Strikingly, deviations in these features (for the vehicles with broken sensors) can be observed up to several months before a breakdown occur. This potentially allows for sufficient time to schedule the vehicle for maintenance and prepare the workshop with relevant components. © 2013 IEEE.

  • 63.
    Caizzone, Stefano
    et al.
    German Aerosp Ctr DLR, Inst Commun & Nav, Wessling, Germany.
    Elmarissi, W.
    German Aerosp Ctr DLR, Inst Commun & Nav, Wessling, Germany.
    Marinho, Marco
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Antreich, F.
    Fed Univ Ceara UFC, Dept Teleinformat Engn, Fortaleza, Ceara, Brazil.
    Direction of arrival estimation performance for compact antenna arrays with adjustable size2017In: 2017 IEEE MTT-S INTERNATIONAL MICROWAVE SYMPOSIUM (IMS), Piscataway: IEEE, 2017, p. 666-669, article id 8058657Conference paper (Refereed)
    Abstract [en]

    The quest for compact antenna arrays able to perform robust beamforming and high resolution direction of arrival (DOA) estimation is pushing the antenna array dimensions to progressively shrink, with effects in terms of reduced performance not only for the antenna but also for beamforming and DOA estimation algorithms, for which their assumptions about the antenna properties do not hold anymore. This work shows the design and development of an antenna array with adjustable mutual distance between the single elements: such setup will allow to scientifically analyse the effects that progressive miniaturization, i.e. progressively smaller mutual distances between the antennas, have on the DOA estimation algorithms, as well as show the improvements obtained by using array interpolation methods, i.e. techniques able to create a virtual array response out of the actual array one, such as to comply with the algorithms’ requirements on the antenna response. © 2017 IEEE.

  • 64.
    Davidsson, Adam
    et al.
    Halmstad University, School of Information Technology.
    Lindbom, Fredrik
    Halmstad University, School of Information Technology.
    Slow-response generator2015Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    Because of environmental pollution, forces the automotive industry constantly reduced emissions requirements legislated by the authorities. Improved techniques for engine control are a must for bringing down emissions. The use of an Exhaust Gas Recirculation (EGR) reduces NOx emissions significantly. Faulty EGR valves affect the emissions negative and therefore needs to be eliminated.

    It is possible to create malfunctions on the EGR valve by modifying the software of the control unit (ECU), but it does not create realistic malfunctions. The problem by modifying the software is that flags and various parameters are set to confirm the malfunction of the ECU. To create actual failure of the EGR valve an external tool to modify the control signal is needed.

    The project's main objective is on a flexible way creating malfunctions on the EGR valve in a truck engine. By investigating engine behavior in a realistic and credible way, one can eliminate malfunctions on the EGR valve. The aim was achieved by a model that has been developed that can, using electronics and a microprocessor read and create a control signal.

    The electronic circuit is controlled by the microprocessor, which can modify the signal and create malfunctions in the form of a slow valve "slow-response". A graphical user interface is used to change and influence the error signal. The circuit with the microprocessor is placed safely in a box to both protect and preserve the components.

    Simulation of Slow response has resulted in an incorrect operated valve being created. Using two different methods a Slow-response can be created. One method is a delay in time, which occurs when the new position is given, the second method is a ramp function when the control signal is gradually increasing. The software can also create an error that mimics a stuck valve of a fixed value. With the above listed methods it is possible in theory to find unknown malfunctions on the EGR valve that influence emissions negatively. 

  • 65.
    Emanuelsson, Herman
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Sjunnesson, Emil
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Fjärrstyrt kamerafäste: HE Remote2013Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    At times when it is not suited to stand by a video camera can be resolved with a remote controlled camera mount. Examples of occasions is due to lack of space at a concert, a solemn ceremony in which someone must stand awkwardly  to to get good image, out in nature where animals shall be filmed without being frightened away or when you have staff shortages, a tight budget and need to control multiple cameras simultaneously. The systems that are available in the amateur market today have different functionality and is not fitting for the above problem or have very limited range and cannot connect to a mobile application.

    This project aims to develop a cost-effective and customized solution for the above problem by developing a remote-controlled camera mount in semi-professional segment where you through a controller and at a later stage with a mobile application controls the camera angle and rotation also called tilt and pan.

    The differences between this and existing solutions are that by using Bluetooth technology can control both the controller and later on also with a mobile application, the reason why it must be able to control both is that it is not always allowed to use cell phones in all environments where you want to film and therefore have a wider range of applications for camera mounting.

  • 66.
    Englund, Cristofer
    et al.
    RISE Viktoria, Gothenburg, Sweden.
    Engdahl, Henrik
    Nimling AB, Askim, Sweden.
    Habibi, Shiva
    Chalmers University of Technology, Gothenburg, Sweden.
    Pettersson, Stefan
    RISE Viktoria, Gothenburg, Sweden.
    Sprei, Frances
    Chalmers University of Technology, Gothenburg, Sweden.
    Voronov, Alexey
    RISE Viktoria, Gothenburg, Sweden.
    Wedlin, Johan
    RISE Viktoria, Gothenburg, Sweden.
    Method for prediction of Utilization Rate of Electric Vehicle Free-Floating Car Sharing Services using Data Mining2018In: 31st International Electric Vehicles Symposium & Exhibition (EVS 31) & International Electric Vehicle Technology Conference 2018 (EVTeC 2018), 2018Conference paper (Refereed)
    Abstract [en]

    Free-floating car sharing is a form of car rental used by people for short periods of time where the cars can be picked up and returned anywhere within a given area. In this paper, we have collected free-floating car sharing data, for electric as well as fossil fueled cars, and data regarding e.g. size of the city, number of cars in the service, etc. The utilization rates of the free-floating car sharing services vary much between the cities, greatly influencing the success of the services. This paper presents the most important factors influencing the utilization rate, and also a methodology to predict the utilization rate for new cities, using data mining based on Random Forests.© EVS 31 & EVTeC 2018.

  • 67.
    Ericson, Stefan K.
    et al.
    University of Skövde, Skövde, Sweden.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Analysis of two visual odometry systems for use in an agricultural field environment2018In: Biosystems Engineering, ISSN 1537-5110, E-ISSN 1537-5129, Vol. 166, p. 116-125Article in journal (Refereed)
    Abstract [en]

    This paper analyses two visual odometry systems for use in an agricultural field environment. The impact of various design parameters and camera setups are evaluated in a simulation environment. Four real field experiments were conducted using a mobile robot operating in an agricultural field. The robot was controlled to travel in a regular back-and-forth pattern with headland turns. The experimental runs were 1.8–3.1 km long and consisted of 32–63,000 frames. The results indicate that a camera angle of 75° gives the best results with the least error. An increased camera resolution only improves the result slightly. The algorithm must be able to reduce error accumulation by adapting the frame rate to minimise error. The results also illustrate the difficulties of estimating roll and pitch using a downward-facing camera. The best results for full 6-DOF position estimation were obtained on a 1.8-km run using 6680 frames captured from the forward-facing cameras. The translation error (x, y, z) is 3.76% and the rotational error (i.e., roll, pitch, and yaw) is 0.0482 deg m−1. The main contributions of this paper are an analysis of design option impacts on visual odometry results and a comparison of two state-of-the-art visual odometry algorithms, applied to agricultural field data. © 2017 IAgrE

  • 68.
    Fan, Yuantao
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Evaluation of Self-Organized Approach for Predicting Compressor Faults in a City Bus Fleet2015In: Procedia Computer Science, ISSN 1877-0509, E-ISSN 1877-0509, Vol. 53, p. 447-456Article in journal (Refereed)
    Abstract [en]

    Managing the maintenance of a commercial vehicle fleet is an attractive application domain of ubiquitous knowledge discovery. Cost effective methods for predictive maintenance are progressively demanded in the automotive industry. The traditional diagnostic paradigm that requires human experts to define models is not scalable to today's vehicles with hundreds of computing units and thousands of control and sensor signals streaming through the on-board controller area network. A more autonomous approach must be developed. In this paper we evaluate the performance of the COSMO approach for automatic detection of air pressure related faults on a fleet of city buses. The method is both generic and robust. Histograms of a single pressure signal are collected and compared across the fleet and deviations are matched against workshop maintenance and repair records. It is shown that the method can detect several of the cases when compressors fail on the road, well before the failure. The work is based on data from a three year long field study involving 19 buses operating in and around a city on the west coast of Sweden. © The Authors. Published by Elsevier B.V.

  • 69.
    Fan, Yuantao
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Nowaczyk, Sławomir
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Rögnvaldsson, Thorsteinn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Using Histograms to Find Compressor Deviations in Bus Fleet Data2014In: The SAIS Workshop 2014 Proceedings, Swedish Artificial Intelligence Society (SAIS) , 2014, p. 123-132Conference paper (Refereed)
    Abstract [en]

    Cost effective methods for predictive maintenance are increasingly demanded in the automotive industry. One solution is to utilize the on-board signals streams on each vehicle and build self-organizing systems that discover data deviations within a fleet. In this paper we evaluate histograms as features for describing and comparing individual vehicles. The results are based on a long-term field test with nineteen city buses operating around Kungsbacka in Halland. The purpose of this work is to investigate ways of discovering abnormal behaviors and irregularities between histograms of on-board signals, here specifically focusing on air pressure. We compare a number of distance measures and analyze the variability of histograms collected over different time spans. Clustering algorithms are used to discover structure in the data and track how this changes over time. As data are compared across the fleet, observed deviations should be matched against (often imperfect) reference data coming from workshop maintenance and repair databases.

  • 70.
    Femling, Frida
    et al.
    Halmstad University, School of Information Technology.
    Olsson, Adam
    Halmstad University, School of Information Technology.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Fruit and Vegetable Identification Using Machine Learning for Retail Application2018In: 2018 14th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS) / [ed] Gabriella Sanniti di Baja, Luigi Gallo, Kokou Yetongnon, Albert Dipanda, Modesto Castrillón-Santana & Richard Chbeir, Los Alamitos: IEEE Computer Society, 2018, p. 9-15Conference paper (Refereed)
    Abstract [en]

    This paper describes an approach of creating a system identifying fruit and vegetables in the retail market using images captured with a video camera attached to the system. The system helps the customers to label desired fruits and vegetables with a price according to its weight. The purpose of the system is to minimize the number of human computer interactions, speed up the identification process and improve the usability of the graphical user interface compared to existing manual systems. The hardware of the system is constituted by a Raspberry Pi, camera, display, load cell and a case. To classify an object, different convolutional neural networks have been tested and retrained. To test the usability, a heuristic evaluation has been performed with several users, concluding that the implemented system is more user friendly compared to existing systems.

  • 71.
    Fernandez-de-Sevilla, R.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, J.
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Forensic Writer Identification Using Allographic Features2010In: Proceedings: 12th International Conference on Frontiers in Handwriting Recognition, ICFHR 2010, Los Alamitos, Calif.: IEEE Computer Society, 2010, p. 308-313Conference paper (Refereed)
    Abstract [en]

    Questioned document examination is extensively used by forensic specialists for criminal identification. This paper presents a writer recognition system based on allographic features operating in identification mode (one-to-many). It works at the level of isolated characters, considering that each writer uses a reduced number of shapes for each one. Individual characters of a writer are manually segmented and labeled by an expert as pertaining to one of 62 alphanumeric classes (10 numbers and 52 letters, including lowercase and uppercase letters), being the particular setup used by the forensic laboratory participating in this work. A codebook of shapes is then generated by clustering and the probability distribution function of allograph usage is the discriminative feature used for recognition. Results obtained on a database of 30 writers from real forensic documents show that the character class information given by the manual analysis provides a valuable source of improvement, justifying the proposed approach. We also evaluate the selection of different alphanumeric channels, showing a dependence between the size of the hit list and the number of channels needed for optimal performance. © 2010 IEEE.

  • 72.
    Fierrez, Julian
    et al.
    Universidad Autonoma de Madrid, Spain.
    Galbally, Javier
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, Javier
    Universidad Autonoma de Madrid, Spain.
    Freire, Manuel R.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ramos, Daniel R.
    Universidad Autonoma de Madrid, Spain.
    Toledano, Doroteo Torre
    Universidad Autonoma de Madrid, Spain.
    Gonzalez-Rodriguez, Joaquin
    Universidad Autonoma de Madrid, Spain.
    Siguenza, Juan A.
    Universidad Autonoma de Madrid, Spain.
    Garrido-Salas, Javier
    Universidad Autonoma de Madrid, Spain.
    Anguiano-Rey, Eloy
    Universidad Autonoma de Madrid, Spain.
    Gonzalez-de-Rivera, Guillermo
    Universidad Autonoma de Madrid, Spain.
    Ribalda, Ricardo
    Universidad Autonoma de Madrid, Spain.
    Faundez-Zanuy, Marcos
    Escuela Universitaria Politecnica de Mataro, Avda. Puig i Cadafalch 101-111, 08303 Mataro, Barcelona, Spain.
    Ortega, Juan Antonio Rosell
    Universidad Politecnica de Cataluña, Esc. Univ. de Ing. Tec. Ind. de Terrassa, C/ Colom 1, 08222 Terrassa, Barcelona, Spain.
    Cardenoso-Payo, Valentín
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Viloria, A.
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Vivaracho, Carlos E.
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Moro, Q. Isaac
    Universidad de Valladolid, Edif. de Tecnicas de la Inf. y las Telecom., Campus Miguel, 47011 Valladolid, Spain.
    Igarza, Juan J.
    Escuela Superior de Ingenieros, Universidad del Pais Vasco, C/ Alameda de Urquijo s/n, 48013 Bilbao, Spain.
    Sanchez, Jon I.
    Escuela Superior de Ingenieros, Universidad del Pais Vasco, C/ Alameda de Urquijo s/n, 48013 Bilbao, Spain.
    Hernaez, Inmaculada
    Escuela Superior de Ingenieros, Universidad del Pais Vasco, C/ Alameda de Urquijo s/n, 48013 Bilbao, Spain.
    Orrite-Urunuela, Carlos
    Computer Vision Laboratory Group, Universidad de Zaragoza, Edif. Ada Byron, C/ Maria de Luna 1, 50018 Zaragoza, Spain.
    Martinez-Contreras, Francisco
    Computer Vision Laboratory Group, Universidad de Zaragoza, Edif. Ada Byron, C/ Maria de Luna 1, 50018 Zaragoza, Spain.
    Gracia-Roche, Juan José
    Computer Vision Laboratory Group, Universidad de Zaragoza, Edif. Ada Byron, C/ Maria de Luna 1, 50018 Zaragoza, Spain.
    BiosecurID: A Multimodal Biometric Database2010In: Pattern Analysis and Applications, ISSN 1433-7541, E-ISSN 1433-755X, Vol. 13, no 2, p. 235-246Article in journal (Refereed)
    Abstract [en]

    A new multimodal biometric database, acquired in the framework of the BiosecurID project, is presented together with the description of the acquisition setup and protocol. The database includes eight unimodal biometric traits, namely: speech, iris, face (still images, videos of talking faces), handwritten signature and handwritten text (on-line dynamic signals, off-line scanned images), fingerprints (acquired with two different sensors), hand (palmprint, contour-geometry) and keystroking. The database comprises 400 subjects and presents features such as: realistic acquisition scenario, balanced gender and population distributions, availability of information about particular demographic groups (age, gender, handedness), acquisition of replay attacks for speech and keystroking, skilled forgeries for signatures, and compatibility with other existing databases. All these characteristics make it very useful in research and development of unimodal and multimodal biometric systems. © Springer-Verlag London Limited 2009.

  • 73.
    Fierrez, Julian
    et al.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Li, Stan Z.Chinese Academy of Sciences, Beijing, China.Ross, ArunMichigan State University, East Lansing, USA.Veldhuis, RaymondUniversity of Twente, Enschede, Netherlands.Alonso-Fernandez, FernandoHalmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.Bigun, JosefHalmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    2016 International Conference on Biometrics (ICB): Proceedings: 13-16 June 2016, Halmstad, Sweden2016Conference proceedings (editor) (Refereed)
  • 74.
    Fierrez-Aguilar, J.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Munoz-Serrano, L. M.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    On the effects of image quality degradation on minutiae- and ridge-based automatic fingerprint recognition2005In: Proceedings: International Carnahan Conference on Security Technology, Piscataway, N.J.: IEEE Press, 2005, p. 79-82Conference paper (Refereed)
    Abstract [en]

    The effect of image quality degradation on the verification performance of automatic fingerprint recognition is investigated. We study the performance of two fingerprint matchers based on minutiae and ridge information under varying fingerprint image quality. The ridge-based system is found to be more robust to image quality degradation than the minutiae-based system for a number of different image quality criteria. © 2005 IEEE.

  • 75.
    Fierrez-Aguilar, Julian
    et al.
    Universidad Politecnica de Madrid, Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Politecnica de Madrid, Madrid, Spain.
    Gonzalez-Rodrigueza, J.
    Universidad Politecnica de Madrid, Madrid, Spain.
    Bigun, Josef
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Kernel-based multimodal biometric verification using quality signals2004In: Proceedings of SPIE: Biometric Technology for Human Identification / [ed] Anil K. Jain, Nalini K. Ratha, 2004, Vol. 5404, p. 544-554Conference paper (Other academic)
    Abstract [en]

    A novel kernel-based fusion strategy is presented. It is based on SVM classifiers, trade-off coefficients introduced in the standard SVM training and testing procedures, and quality measures of the input biometric signals. Experimental results on a prototype application based on voice and fingerprint traits are reported. The benefits of using the two modalities as compared to only using one of them are revealed. This is achieved by using a novel experimental procedure in which multi-modal verification performance tests are compared with multi-probe tests of the individual subsystems. Appropriate selection of the parameters of the proposed quality-based scheme leads to a quality-based fusion scheme outperforming the raw fusion strategy without considering quality signals. In particular, a relative improvement of 18% is obtained for small SVM training set size by using only fingerprint quality labels.

  • 76.
    Galbally, J.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Fingerprint Liveness Detection Based on Quality Measures2009In: 2009 1st IEEE International Conference on Biometrics, Identity and Security, BIdS 2009, Piscataway, N.J.: IEEE Press, 2009, p. 1-8Conference paper (Refereed)
    Abstract [en]

    A new fingerprint parameterization for liveness detection based on quality measures is presented. The novel feature set is used in a complete liveness detection system and tested on the development set of the LivDET competition, comprising over 4,500 real and fake images acquired with three ditTerent optical sensors. The proposed solution proves to be robust to the multi-sensor scenario, and presents an overall rate of 93% of correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake.

  • 77.
    Galbally, Javier
    et al.
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, Julian
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, Javier
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    A High Performance Fingerprint Liveness Detection Method Based on Quality Related Features2012In: Future generations computer systems, ISSN 0167-739X, E-ISSN 1872-7115, Vol. 28, no 1, p. 311-321Article in journal (Refereed)
    Abstract [en]

    A new software-based liveness detection approach using a novel fingerprint parameterization based on quality related features is proposed. The system is tested on a highly challenging database comprising over 10,500 real and fake images acquired with five sensors of different technologies and covering a wide range of direct attack scenarios in terms of materials and procedures followed to generate the gummy fingers. The proposed solution proves to be robust to the multi-scenario dataset, and presents an overall rate of 90% correctly classified samples. Furthermore, the liveness detection method presented has the added advantage over previously studied techniques of needing just one image from a finger to decide whether it is real or fake. This last characteristic provides the method with very valuable features as it makes it less intrusive, more user friendly, faster and reduces its implementation costs. © 2010 Elsevier B.V. All rights reserved.

  • 78.
    Galbally, Javier
    et al.
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, Julian
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Martinez-Diaz, Marcos
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Evaluation of Direct Attacks to Fingerprint Verification Systems2011In: Telecommunications Systems, ISSN 1018-4864, E-ISSN 1572-9451, Vol. 47, no 3, p. 243-254Article in journal (Refereed)
    Abstract [en]

    The vulnerabilities of fingerprint-based recognition systems to direct attacks with and without the cooperation of the user are studied. Two different systems, one minutiae-based and one ridge feature-based, are evaluated on a database of real and fake fingerprints. Based on the fingerprint images quality and on the results achieved on different operational scenarios, we obtain a number of statistically significant observations regarding the robustness of the systems. © 2010 Springer Science+Business Media, LLC.

  • 79.
    Galbally-Herrero, J.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Rodriguez-Gonzalez, J. D.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Tapiador, M.
    Universidad Autonoma de Madrid, Spain.
    On the vulnerability of fingerprint verification systems to fake fingerprint attacks2006In: Proceedings: International Carnahan Conference on Security Technology, Piscataway, N.J.: IEEE Press, 2006, p. 130-136Conference paper (Refereed)
    Abstract [en]

    A new method to generate gummy fingers is presented. A medium-size fake fingerprint database is described and two different fingerprint verification systems are evaluated on it. Three different scenarios are considered in the experiments, namely: enrollment and test with real fingerprints, enrollment and test with fake fingerprints, and enrollment with real fingerprints and test with fake fingerprints. Results for an optical and a thermal sweeping sensors are given. Both systems are shown to be vulnerable to direct attacks. © 2006 IEEE.

  • 80.
    Gangwar, Abhishek
    et al.
    Centre for Development of Advanced Computing (CDAC), Mumbai, India.
    Joshi, Akanksha
    Centre for Development of Advanced Computing (CDAC), Mumbai, India.
    Singh, Ashutosh
    Centre for Development of Advanced Computing (CDAC), Mumbai, India.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bigun, Josef
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    IrisSeg: A Fast and Robust Iris Segmentation Framework for Non-Ideal Iris Images2016In: 2016 INTERNATIONAL CONFERENCE ON BIOMETRICS (ICB) / [ed] J. Fierrez, S.Z. Li, A. Ross, R. Veldhuis, F. Alonso-Fernandez, J. Bigun, Piscataway: IEEE, 2016Conference paper (Refereed)
    Abstract [en]

    This paper presents a state-of-the-art iris segmentation framework specifically for non-ideal irises. The framework adopts coarse-to-fine strategy to localize different boundaries. In the approach, pupil is coarsely detected using an iterative search method exploiting dynamic thresholding and multiple local cues. The limbic boundary is first approximated in polar space using adaptive filters and then refined in Cartesianspace. The framework is quite robust and unlike the previously reported works, does notrequire tuning of parameters for different databases. The segmentation accuracy (SA) is evaluated using well known measures; precision, recall and F-measure, using the publicly available ground truth data for challenging iris databases; CASIAV4-Interval, ND-IRIS-0405, and IITD. In addition, the approach is also evaluated on highly challenging periocular images of FOCS database. The validity of proposed framework is also ascertained by providing comprehensive comparisons with classical approaches as well asstate-of-the-art methods such as; CAHT, WAHET, IFFP, GST and Osiris v4.1. The results demonstrate that our approach provides significant improvements in segmentation accuracy as well as in recognition performance that too with lower computational complexity. © 2016 IEEE.

  • 81.
    Garcia-Salicetti, S.
    et al.
    Institut National des Tëlëcommunications, France.
    Fierrez-Aguilar, J.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Vielhauer, C.
    Otto-Von-Guericke University of Magdeburg, Germany.
    Guest, R.
    University of Kent, Canterbur, United Kingdom.
    Allano, L.
    Institut National des Tëlëcommunications, France.
    Trung, T. Doan
    Institut National des Tëlëcommunications, France.
    Scheidat, T.
    Otto-Von-Guericke University of Magdeburg, Germany.
    Van, B. Ly
    Institut National des Tëlëcommunications, France.
    Dittmann, J.
    Otto-Von-Guericke University of Magdeburg, Germany.
    Dorizzi, B.
    Institut National des Tëlëcommunications, France.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Gonzalez-Rodriguez, J.
    Universidad Autonoma de Madrid, Spain.
    Castiglione, M. Bacile di
    University of Kent, Canterbur, United Kingdom.
    Fairhurst, M.
    University of Kent, Canterbur, United Kingdom.
    Biosecure reference systems for on-line signature verification: A study of complementarity2007In: Annales des télécommunications, ISSN 0003-4347, E-ISSN 1958-9395, Vol. 62, no 1-2, p. 36-61Article in journal (Refereed)
    Abstract [en]

    In this paper, we present an integrated research study in On-line Signature Verification undertaken by several teams that participate in the BioSecure Network of Excellence. This integrated work, started during the First BioSecure Residential Workshop, has as main objective the development of an On-line Signature Verification evaluation platform. As a first step, four On-line Signature Verification Systems based on different approaches are evaluated and compared following the same experimental protocol on MCYT signature database, which is the largest existing on-line western signature database publicly available with 16 500 signatures from 330 clients. A particular focus of work documented in this paper is multi-algorithmic fusion in order to study the complementarity of the approaches involved. To this end, a simple fusion method based on the Mean Rule is used after a normalization phase.

  • 82.
    Garcia-Salicetti, S.
    et al.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Houmani, N.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Ly-Van, B.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Dorizzi, B.
    TELECOM SudParis (ex GET-INT), 9, rue Charles Fourier, 91011, Evry, France .
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Fierrez, J.
    Univ. Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Univ. Autonoma de Madrid, Spain.
    Vielhauer, C.
    Univ. Autonoma de Madrid, Spain.
    Scheidat, T.
    Univ. Autonoma de Madrid, Spain.
    Online Handwritten Signature Verification2009In: Guide to Biometric Reference Systems and Performance Evaluation / [ed] Petrovska-Delacretaz, D.; Chollet, G.; Dorizzi, B., London: Springer London, 2009, p. 125-165Chapter in book (Other academic)
    Abstract [en]

    In this chapter, we first provide an overview of the existing main approaches, databases, evaluation campaigns and the remaining challenges in online handwritten signature verification. We then propose a new benchmarking framework for online signature verification by introducing the concepts of “Reference Systems”, “Reference Databases” and associated “Reference Protocols.” Finally, we present the results of several approaches within the proposed evaluation framework. Among them are also present the best approaches within the first international Signature Verification Competition held in 2004 (SVC’2004), Dynamic Time Warping and Hidden Markov Models. All these systems are evaluated first within the benchmarking framework and also with other relevant protocols. Experiments are also reported on two different databases (BIOMET and MCYT) showing the impact of time variability for online signature verification. The two reference systems presented in this chapter are also used and evaluated in the BMEC’2007 evaluation campaign, presented in Chap11. ©Springer 2009

  • 83.
    Gelzinis, Adas
    et al.
    Kaunas University of Technology, Kaunas, Lithuania.
    Verikas, Antanas
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Kaunas University of Technology, Kaunas, Lithuania.
    Bacauskiene, Marija
    Kaunas University of Technology, Kaunas, Lithuania.
    Vaiciukynas, Evaldas
    Kaunas University of Technology, Kaunas, Lithuania.
    Learning Accurate Active Contours2013In: Engineering Applications of Neural Networks: 14th International Conference, EANN 2013, Halkidiki, Greece, September 13-16, 2013 Proceedings, Part I / [ed] Lazaros Iliadis, Harris Papadopoulos & Chrisina Jayne, Berlin Heidelberg: Springer Berlin/Heidelberg, 2013, Vol. 383, p. 396-405Conference paper (Refereed)
    Abstract [en]

    Focus of research in Active contour models (ACM) area is mainly on development of various energy functions based on physical intuition. In this work, instead of designing a new energy function, we generate a multitude of contour candidates using various values of ACM parameters, assess their quality, and select the most suitable one for an object at hand. A random forest is trained to make contour quality assessments. We demonstrate experimentally superiority of the developed technique over three known algorithms in the P. minimum cells detection task solved via segmentation of phytoplankton images. © Springer-Verlag Berlin Heidelberg 2013.

  • 84.
    GHIMIRE, SWATANTRA
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Speech Intelligibility Measurement on the basis of ITU-T Recommendation P.8632012Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Objective speech intelligibility measurement techniques like AI (Articulation Index) and AI based STI (Speech Transmission Index) fail to assess speech intelligibility in modern telecommunication networks that use several non-linear processing for enhancing speech. Moreover, these techniques do not allow prediction of single individual CVC (Consonant Vowel Consonant) word intelligibility scores. ITU-T P.863 standard [1], which was developed for assessing speech quality, is used as a starting point to develop a simple new model for predicting subjective speech intelligibility of individual CVC words. Subjective intelligibility measurements were carried out for a large set of speech degradations. The subjective test uses single CVC word presentations in an eight alternative closed response set experiment. Subjects assess individual degraded CVC words and an average of correct recognition is used as the intelligibility score for a particular CVC word. The first subjective database uses CVC words that have variations in the first consonant i.e. /C/ous (represented as "kæʊs" using International Phonetic Association phonetic alphabets). This database is used for developing the objective model, while a new database based on VC words (Vowel Consonant) that uses variations in the second consonant (a/C/ e.g. aH, aL) is used for validating the model.

    ITU-T P.863 shows very poor results with a correlation of 0.30 for the first subjective database. A first extension to make P.863 suited for intelligibility prediction is done by restructuring speech material to meet the temporal structure requirements (speech+silence+speech) set for standard P.863 measurements. The restructuring is done by concatenating every original and degraded CVC word with itself. There is no significant improvement in correlation (0.34) when using P.863 on the restructured first subjective database (speech material meets temporal requirements).  In this thesis a simple model based on P.863 is developed for assessing intelligibility of individual CVC words. The model uses a linear combination of a simple time clipping indicator (missing speech parts) and a “Good frame count” indicator which is based on the local perceptual (frame by frame) signal to noise ratio. Using this model on the restructured first database, a reasonably good correlation of 0.81 is seen between subjective scores and the model output values. For the validation database, a correlation of around 0.76 is obtained. Further validation on an existing database at TNO, which uses time clipping degradation only, shows an excellent correlation of 0.98.

    Although a reasonably good correlation is seen on the first database and the validation database, it is too low for reliable measurements. Further validation and development is required, nevertheless the results show that a perception-based technique that uses internal representations of signals can be used for predicting subjective intelligibility scores of individual CVC words.

  • 85.
    Gholami Shahbandi, Saeed
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Semantic Mapping in Warehouses2016Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    This thesis and appended papers present the process of tacking the problem of environment modeling for autonomous agent. More specifically, the focus of the work has been semantic mapping of warehouses. A semantic map for such purpose is expected to be layout-like and support semantics of both open spaces and infrastructure of the environment. The representation of the semantic map is required to be understandable by all involved agents (humans, AGVs and WMS.) And the process of semantic mapping is desired to lean toward full-autonomy, with minimum input requirement from human user. To that end, we studied the problem of semantic annotation over two kinds of spatial map from different modalities. We identified properties, structure, and challenges of the problem. And we have developed representations and accompanied methods, while meeting the set criteria. The overall objective of the work is “to develop and construct a layer of abstraction (models and/or decomposition) for structuring and facilitate access to salient information in the sensory data. This layer of abstraction connects high level concepts to low-level sensory pattern.” Relying on modeling and decomposition of sensory data, we present our work on abstract representation for two modalities (laser scanner and camera) in three appended papers. Feasibility and the performance of the proposed methods are evaluated over data from real warehouse. The thesis conclude with summarizing the presented technical details, and drawing the outline for future work.

  • 86.
    Gholami Shahbandi, Saeed
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Modeling of a Large Structured Environment: With a Repetitive Canonical Geometric-Semantic Model2014In: Advances in Autonomous Robotics Systems: 15th Annual Conference, TAROS 2014, Birmingham, UK, September 1-3, 2014. Proceedings / [ed] Michael Mistry, Aleš Leonardis, Mark Witkowski & Chris Melhuish, Heidelberg: Springer, 2014, Vol. 8717, p. 1-12Conference paper (Refereed)
    Abstract [en]

    AIMS project attempts to link the logistic requirements of an intelligent warehouse and state of the art core technologies of automation, by providing an awareness of the environment to the autonomous systems and vice versa. In this work we investigate a solution for modeling the infrastructure of a structured environment such as warehouses, by the means of a vision sensor. The model is based on the expected pattern of the infrastructure, generated from and matched to the map. Generation of the model is based on a set of tools such as closed-form Hough transform, DBSCAN clustering algorithm, Fourier transform and optimization techniques. The performance evaluation of the proposed method is accompanied with a real world experiment. © 2014 Springer International Publishing.

  • 87.
    Gholami Shahbandi, Saeed
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Philippsen, Roland
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Sensor Based Adaptive Metric-Topological Cell Decomposition Method for Semantic Annotation of Structured Environments2014In: 2014 13th International Conference on Control Automation Robotics & Vision (ICARCV), Piscataway, NJ: IEEE Press, 2014, p. 1771-1777, article id 7064584Conference paper (Refereed)
    Abstract [en]

    A fundamental ingredient for semantic labeling is a reliable method for determining and representing the relevant spatial features of an environment. We address this challenge for planar metric-topological maps based on occupancy grids. Our method detects arbitrary dominant orientations in the presence of significant clutter, fits corresponding line features with tunable resolution, and extracts topological information by polygonal cell decomposition. Real-world case studies taken from the target application domain (autonomous forklift trucks in warehouses) demonstrate the performance and robustness of our method, while results from a preliminary algorithm to extract corridors, and junctions, demonstrate its expressiveness. Contribution of this work starts with the formulation of metric-topological surveying of environment, and a generic n-direction planar representation accompanied with a general method for extracting it from occupancy map. The implementation also includes some semantic labels specific to warehouse like environments. © 2014 IEEE.

  • 88.
    Gilperez, A.
    et al.
    Universidad Autonoma de Madrid, Spain.
    Alonso-Fernandez, Fernando
    Escuela Politecnica Superior, Univ. Autonoma de Madrid, Spain.
    Pecharroman, S.
    Universidad Autonoma de Madrid, Spain.
    Fierrez, J.
    Universidad Autonoma de Madrid, Spain.
    Ortega-Garcia, J.
    Universidad Autonoma de Madrid, Spain.
    Off-line Signature Verification Using Contour Features2008In: Proceedings: eleventh International Conference on Frontiers in Handwriting Recognition, Montréal, Québec - Canada, August 19-21, 2008, Montréal: CENPARMI, Concordia University , 2008Conference paper (Refereed)
    Abstract [en]

    An off-line signature verification system based on contour features is presented. It works at the local image level, and encodes directional properties of signature contours and the length of regions enclosed inside letters. Results obtained on a sub-corpus of the MCYT signature database shows that directional-based features work much better than length-based features. Results are comparable to existing approaches based on different features. It is also observed that combination of the proposed features does not provide improvements in performance, maybe to some existing correlation among them.

  • 89.
    Gonzalez, Ramon
    et al.
    Massachusetts Institute of Technology, Cambridge, MA, USA.
    Byttner, Stefan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Iagnemma, Karl
    Massachusetts Institute of Technology, Cambridge, MA, USA.
    Comparison of Machine Learning Approaches for Soil Embedding Detection of Planetary Exploration Rovers2016In: Proceedings of the 8th ISTVS Americas Conference, Detroit, September 12-14, 2016., 2016Conference paper (Refereed)
    Abstract [en]

    This paper analyzes the advantages and limitations of known machine learning approaches to cope with the problem of incipient rover embedding detection based on propioceptive signals. In particular, two supervised learning approaches (Support Vector Machines and Feed-forward Neural Networks) are compared to two unsupervised learning approaches (K-means and Self-Organizing Maps) in order to identify various degrees of slip (e.g. low slip, moderate slip, high slip). A real dataset collected by a single-wheel testbed available at MIT has been used to validate each strategy. The SVM algorithm achieves the best performance (accuracy >95 %). However, the SOM algorithm represents a better solution in terms of accuracy and the need of hand-labeled data for training the classifier (accuracy >84 %).

  • 90.
    Gonzalez-Sosa, Ester
    et al.
    Nokia Bell-Labs, Madrid, Spain & Universidad Autonoma de Madrid, Madrid, Spain.
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Vera-Rodriguez, Ruben
    Universidad Autonoma de Madrid, Madrid, Spain.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Facial Soft Biometrics for Recognition in the Wild: Recent Works, Annotation and Evaluation2018In: IEEE Transactions on Information Forensics and Security, ISSN 1556-6013, E-ISSN 1556-6021, Vol. 13, no 8, p. 2001-2014Article in journal (Refereed)
    Abstract [en]

    The role of soft biometrics to enhance person recognition systems in unconstrained scenarios has not been extensively studied. Here, we explore the utility of the following modalities: gender, ethnicity, age, glasses, beard, and moustache. We consider two assumptions: 1) manual estimation of soft biometrics and 2) automatic estimation from two commercial off-the-shelf systems (COTS). All experiments are reported using the labeled faces in the wild (LFW) database. First, we study the discrimination capabilities of soft biometrics standalone. Then, experiments are carried out fusing soft biometrics with two state-of-the-art face recognition systems based on deep learning. We observe that soft biometrics is a valuable complement to the face modality in unconstrained scenarios, with relative improvements up to 40%/15% in the verification performance when using manual/automatic soft biometrics estimation. Results are reproducible as we make public our manual annotations and COTS outputs of soft biometrics over LFW, as well as the face recognition scores. © 2018 IEEE.

  • 91.
    Gonzalez-Sosa, Ester
    et al.
    Universidad Autonoma de Madrid, Madrid, Spain.
    Vera-Rodriguez, Ruben
    Universidad Autonoma de Madrid, Madrid, Spain.
    Fierrez, Julian
    Universidad Autonoma de Madrid, Madrid, Spain.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Patel, Vishal M.
    Rutgers University, NJ, USA.
    Exploring Body Texture From mmW Images for Person Recognition2019In: IEEE Transactions on Biometrics, Behavior, and Identity Science, E-ISSN 2637-6407, Vol. 1, no 2, p. 139-151Article in journal (Refereed)
    Abstract [en]

    Imaging using millimeter waves (mmWs) has many advantages including the ability to penetrate obscurants, such as clothes and polymers. After having explored shape information retrieved from mmW images for person recognition, in this paper we aim to gain some insight about the potential of using mmW texture information for the same task, considering not only the mmW face, but also mmW torso and mmW wholebody. We report experimental results using the mmW TNO database consisting of 50 individuals based on both hand-crafted and learned features from Alexnet and VGG-face pretrained convolutional neural networks (CNNs) models. First, we analyze the individual performance of three mmW body parts, concluding that: 1) mmW torso region is more discriminative than mmW face and the whole body; 2) CNN features produce better results compared to hand-crafted features on mmW faces and the entire body; and 3) hand-crafted features slightly outperform CNN features on mmW torso. In the second part of this paper, we analyze different multi-algorithmic and multi-modal techniques, including a novel CNN-based fusion technique, improving verification results to 2% EER and identification rank-1 results up to 99%. Comparative analyses with mmW body shape information and face recognition in the visible and NIR spectral bands are also reported.

  • 92.
    Grip, Andreas
    Halmstad University, School of Information Technology.
    Kraftmätning på cykelpedal2018Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    This report will describe the development of a subsystem for force measurement on bicycle pedals. The force is going to be used as a control parameter in a motor controller to control an electric motor on an electric bicycle. The report focuses on force measurement and will not process any control system. There has also been a survey of alternative power supplies to the circuit boards to be used in this project. Energy Harvesting has been investigated as an alternative source. The aim of the project is to measure the force applied on the pedal in a good way for use in a control system.This work resulted in that the force applied on the pedals was measured on the crank arms. The force was being measured by strain gauge sensors in a test rig designed in this project. The force signal can be used in the intended control system. This report has explained when, during a pedal stroke, the force should be measured. Processing of the signal will be done furthermore in the motor controller to fit the requirements set by the control system.

  • 93.
    Hansson, Jörgen
    et al.
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Svensson, Magnus
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Rögnvaldsson, Thorsteinn
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Byttner, Stefan
    Volvo Group Trucks Technology, Göteborg, Sweden.
    Remote Diagnosis Modelling2008Patent (Other (popular science, discussion, etc.))
    Abstract [en]

    A diagnosis and maintenance method, a diagnosis and maintenance assembly comprising a central server and a system, and a computer program for diagnosis and maintenance for a plurality of systems, particularly for a plurality of vehicles, wherein each system provides at least one system-related signal which provides the basis for the diagnosis and/or maintenance of/for the system are provided. The basis for diagnosis and/or maintenance is determined by determining for each system at least one relation between the system-related signals, comparing the compatible determined relations, determining for the plurality of systems based on the result of the comparison which relations are significant relations and providing a diagnosis and/or maintenance decision based on the determined significant relations.

  • 94.
    Hashemzadeh, Parham
    Halmstad University, School of Business and Engineering (SET), Mechanical Engineering and Industrial Design (MTEK), Fotonik.
    Parametric Reconstruction of Objects Using Microwave Measurements2009Doctoral thesis, comprehensive summary (Other academic)
  • 95.
    Hedenberg, Klas
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. University of Skövde, Skövde, Sweden.
    Obstacle Detection for Driverless Trucks in Industrial Environments2014Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    With an increased demand on productivity and safety in industry, new issues in terms of automated material handling arise. This results in industries not having a homogenous fleet of trucks and driven and driverless trucks are mixed in a dynamic environment. Driven trucks are more flexible than driverless trucks, but are also involved in more accidents. A transition from driven to driverless trucks can increase safety, but also productivity in terms of fewer accidents and more accurate delivery. Hence, reliable and standardized solutions that avoid accidents are important to achieve high productivity and safety. There are two different safety standards for driverless trucks for Europe (EN1525) and U.S. (B56.5–2012) and they have developed differently. In terms of obstacles, they both consider contact with humans. However, a machinery-shaped object has recently been added to the U.S. standard (B56.5–2012). The U.S. standard also considers different materials for different sensors and non-contact sensors. For obstacle detection, the historical contact-sensitive mechanical bumpers as well as the traditional laser scanner used today both have limitations – they do not detect hanging objects. In this work we have identified several thin objects that are of interest in an industrial environment. A test apparatus with a thin structure is introduced for a more uniform way to evaluate sensors. To detect thin obstacles, we used a standard setup of a stereo system and developed this further to a trinocular system (a stereo system with three cameras). We also propose a method to evaluate 3D sensors based on the information from a 2D range sensor. The 3D model is created by measuring the position of a reflector with known position to an object with a known size. The trinocular system, a 3D TOF camera and a Kinect sensor are evaluated with this method. The results showed that the method can be used to evaluate sensors. It also showed that 3D sensor systems have potential to be used on driverless trucks to detect obstacles, initially as a complement to existing safety classed sensors. To improve safety and productivity, there is a need for harmonization of the European and the U.S. safety standards. Furthermore, parallel development of sensor systems and standards is needed to make use of state-of-the-art technology for sensors.

  • 96.
    Hedenberg, Klas
    et al.
    University of Skövde, School of Technology and Society, Skövde, Sweden.
    Baerveldt, Albert-Jan
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Stereo vision-based collision avoidance2004In: The 9th Mechatronics Forum International Conference: Conference Proceedings, Ankara: Atılım University , 2004, p. 259-270Conference paper (Refereed)
    Abstract [en]

    This paper investigates whether a stereo vision system based on points of interest is robust enough to detect obstacles for applications like a mobile robot in an industrial environment and for the visually impaired. Points of interest are extracted with a known method, called KLT. Two algorithms to solve the correspondence problem (Sum of Squared Difference and Variance Normalized Correlation) are used and evaluated as well as a combination of the two. An improvement is made if the two algorithms are combined. The tests show that stereo vision based on points of interest only can be used robustly for obstacle detection if there is enough texture on the obstacle. Otherwise too few points of interest on the object are detected and a reliable estimation of the distance to the object cannot be made.

  • 97.
    Hedenberg, Klas
    et al.
    Skövde University, Skövde, Sweden.
    Åstrand, Björn
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    3D Sensors on Driverless Trucks for Detection of Overhanging Objects in the Pathway2015In: Autonomous Industrial Vehicles: From the Laboratory to the Factory Floor / [ed] Roger Bostelman & Elena Messina, Conshohocken: ASTM International, 2015, p. 41-56Chapter in book (Refereed)
    Abstract [en]

    Human-operated and driverless trucks often collaborate in a mixed work space in industries and warehouses. This is more efficient and flexible than using only one kind of truck. However, since driverless trucks need to give way to trucks, a reliable detection system is required. Several challenges exist in the development of an obstacle detection system in an industrial setting. The first is to select interesting situations and objects. Overhanging objects are often found in industrial environments, e.g. tines on a forklift. Second is choosing a detection system that has the ability to detect those situations. The traditional laser scanner situated two decimetres above the floor does not detect overhanging objects. Third is to ensure that the perception system is reliable. A solution used on trucks today is to mount a 2D laser scanner on the top of the truck and tilt the scanner towards the floor. However, objects at the top of the truck will be detected too late and a collision cannot always be avoided. Our aim is to replace the upper 2D laser scanner with a 3D camera, structural light or time-of-flight (TOF) camera. It is important to maximize the field of view in the desired detection volume. Hence, the placement of the sensor is important. We conducted laboratory experiments to check and compare the various sensors’ capabilities for different colors, used tines and a model of a tine in a controlled industrial environment. We also conducted field experiments in a warehouse. The conclusion is that both the tested structural light and TOF sensors have problems to detect black items that is nonperpendicular to the sensor and at the distance of interest. It is important to optimize the light economy, meaning the illumination power, field of view and exposure time in order to detect as many different objects as possible. Copyright © 2016 by ASTM International

  • 98.
    Helldin, Tove
    et al.
    University of Skövde, Skövde, Sweden.
    Riveiro, Maria
    University of Skövde, Skövde, Sweden.
    Pashami, Sepideh
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Falkman, Göran
    University of Skövde, Skövde, Sweden.
    Byttner, Stefan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Slawomir, Nowaczyk
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Supporting Analytical Reasoning: A Study from the Automotive Industry2016In: Human Interface and the Management of Information: Applications and Services: 18th International Conference, HCI International 2016: Toronto, Canada, July 17-22, 2016. Proceedings, Part II / [ed] Sakae Yamamoto, Cham: Springer, 2016, Vol. 9735, p. 20-31Conference paper (Refereed)
    Abstract [en]

    In the era of big data, it is imperative to assist the human analyst in the endeavor to find solutions to ill-defined problems, i.e. to “detect the expected and discover the unexpected” (Yi et al., 2008). To their aid, a plethora of analysis support systems is available to the analysts. However, these support systems often lack visual and interactive features, leaving the analysts with no opportunity to guide, influence and even understand the automatic reasoning performed and the data used. Yet, to be able to appropriately support the analysts in their sense-making process, we must look at this process more closely. In this paper, we present the results from interviews performed together with data analysts from the automotive industry where we have investigated how they handle the data, analyze it and make decisions based on the data, outlining directions for the development of analytical support systems within the area. © Springer International Publishing Switzerland 2016.

  • 99.
    Hernandez-Diaz, Kevin
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bigun, Josef
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Cross Spectral Periocular Matching using ResNet Features2019Conference paper (Refereed)
    Abstract [en]

    Periocular recognition has gained attention in the last years thanks to its high discrimination capabilities in less constraint scenarios than other ocular modalities. In this paper we propose a method for periocular verification under different light spectra using CNN features with the particularity that the network has not been trained for this purpose. We use a ResNet-101 pretrained model for the ImageNet Large Scale Visual Recognition Challenge to extract features from the IIITD Multispectral Periocular Database. At each layer the features are compared using χ 2 distance and cosine similitude to carry on verification between images, achieving an improvement in the EER and accuracy at 1% FAR of up to 63.13% and 24.79% in comparison to previous works that employ the same database. In addition to this, we train a neural network to match the best CNN feature layer vector from each spectrum. With this procedure, we achieve improvements of up to 65% (EER) and 87% (accuracy at 1% FAR) in cross-spectral verification with respect to previous studies.

  • 100.
    Hernandez-Diaz, Kevin
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Alonso-Fernandez, Fernando
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Bigun, Josef
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Cross-Spectral Biometric Recognition with Pretrained CNNs as Generic Feature Extractors2019Conference paper (Other academic)
    Abstract [en]

    Periocular recognition has gained attention in the last years thanks to its high discrimination capabilities in less constraint scenarios than face or iris. In this paper we propose a method for periocular verification under different light spectra using CNN features with the particularity that the network has not been trained for this purpose. We use a ResNet-101 pretrained model for the ImageNet Large Scale Visual Recognition Challenge to extract features from the IIITD Multispectral Periocular Database. At each layer the features are compared using χ 2 distance and cosine similitude to carry on verification between images, achieving an improvement in the EER and accuracy at 1% FAR of up to 63.13% and 24.79% in comparison to previous works that employ the same database. In addition to this, we train a neural network to match the best CNN feature layer vector from each spectrum. With this procedure, we achieve improvements of up to 65% (EER) and 87% (accuracy at 1% FAR) in cross-spectral verification with respect to previous studies.

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