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  • 1.
    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.

  • 2.
    Cooney, Martin
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Karlsson, Stefan M.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Impressions of Size-Changing in a Companion Robot2015In: PhyCS 2015 – 2nd International Conference on Physiological Computing Systems, Proceedings / [ed] Hugo Plácido da Silva, Pierre Chauvet, Andreas Holzinger, Stephen Fairclough & Dennis Majoe, SciTePress, 2015, p. 118-123Conference paper (Refereed)
    Abstract [en]

    Physiological data such as head movements can be used to intuitively control a companion robot to perform useful tasks. We believe that some tasks such as reaching for high objects or getting out of a person’s way could be accomplished via size changes, but such motions should not seem threatening or bothersome. To gain insight into how size changes are perceived, the Think Aloud Method was used to gather typical impressions of a new robotic prototype which can expand in height or width based on a user’s head movements. The results indicate promise for such systems, also highlighting some potential pitfalls.

  • 3.
    Hoang, Hoai
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Buttazzo, Giorgio
    Real-Time Systems Laboratory Scuola Superiore Sant’Anna Pisa, Italy.
    Jonsson, Magnus
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Karlsson, Stefan
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Computing the minimum EDF feasible deadline in periodic systems2006In: 12th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, 2006. Proceedings, Los Alamitos, Calif.: IEEE Press, 2006, p. 125-134Conference paper (Refereed)
    Abstract [en]

    In most real-time applications, deadlines are artifices that need to be enforced to meet different performance requirements. For example, in periodic task sets, jitter requirements can be met by assigning suitable relative deadlines and guaranteeing the feasibility of the schedule. This paper presents a method (called minD) for calculating the minimum EDF-feasible deadline of a real-time task. More precisely, given a set of periodic tasks with hard real-time requirements, which is feasible under EDF, the proposed algorithm allows computing the shortest deadline that can be assigned to an arbitrary task in the set, or to a new incoming task (periodic or aperiodic), still preserving the EDF feasibility of the new task set. The algorithm has a pseudo polynomial complexity and handles arbitrary relative deadlines, which can be less than, equal to, or greater than periods.

  • 4.
    Hoang, Hoai
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Karlsson, Stefan
    Jonsson, Magnus
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE).
    Minimum EDF-feasible deadline calculation with low-time complexity2004In: RTSS 2004 WIP Proceedings, The 25th IEEE International Real-Time Systems Symposium, Lisbon, Portugal, Dec. 5-8, 2004, 2004Conference paper (Refereed)
    Abstract [en]

    We present a method for calculating the minimum EDF-feasible deadline. The algorithm targets periodic tasks with hard real-time guarantees, that are to be feasibly scheduled with EDF (Earliest Deadline First). The output is the smallest possible deadline required for feasibility, of the task most recently requested. The good thing with our algorithm is that it has the same timecomplexity as the regular EDF feasibility test, when deadlines are not assumed to be equal to the periods of the periodic tasks.

  • 5.
    Karlsson, Stefan
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS), Intelligent Systems´ laboratory.
    Real-Time optical flow2013Other (Other academic)
  • 6.
    Karlsson, Stefan
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Multiscale complex moments of the local power spectrum2007In: Journal of the Optical Society of America A, ISSN 0740-3232, Vol. 24, no 3, p. 618-625Article in journal (Refereed)
    Abstract [en]

    Complex moments of the local power spectrum (CMP) are investigated in a multiscale context. The multiscale CMPs are shown to approximate well the 1D angular Fourier transform of the band in question. This observation is used to derive further properties of the power spectrum in terms of texture orientations or n-folded symmetry patterns. A method is presented to approximate the power spectrum using only separable filtering in the spatial domain. Interesting implications to the Gabor decomposition are shown. The number of orientations in the filter bank is related to the order of n-folded symmetry detectable. Furthermore, the multiscale CMPs can be estimated incrementally in the spatial domain, which is both fast and reliable. Experiments on power spectrum estimation, orientation estimation, and texture segmentation are presented.

  • 7.
    Karlsson, Stefan
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Synthesis and detection of log-spiral codes2011Conference paper (Other academic)
    Abstract [en]

    Simultaneous positioning and identifying objects accurately and reliably is a fundamental problem in computer vision. General solutions to this problem is still challenging. For certain applications to achieve high accuracy and reliability in both tasks can be achieved if the objects can be labeled, e.g. multiple simultaneous robot tracking and navigation. We suggest a labeling technique using spiral patterns for optimal position estimation and identity recognition using the generalized structure tensor and tresholds. The technique adapts the synthesis of the labels to the frequency characteristics of the detection method. The approach has been implemented and tested by an over-head camera to track and control 8 robots in real-time.

  • 8.
    Karlsson, Stefan
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Texture analysis of multiscale complex moments of the local power spectrum2005Report (Other academic)
  • 9.
    Karlsson, Stefan M.
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Bigun, Josef
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Lip-motion events analysis and lip segmentation using optical flow2012Conference paper (Refereed)
    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.

  • 10.
    Karlsson, Stefan M.
    et al.
    Halmstad University, School of Information Science, Computer and Electrical Engineering (IDE), Halmstad Embedded and Intelligent Systems Research (EIS).
    Pont, Sylvia C.
    Pi-Lab., Industrial Design Engineering, Delft University of Technology, Landbergstraat 15, Delft 2628 CE, Netherlands.
    Koenderink, Jan J.
    Pi-Lab., Electrical Engineering, Mathematics and Computer Science, Delft University of Technology, Mekelweg 4, Delft 2028 CD, Netherlands.
    Zisserman, Andrew
    Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, United Kingdom.
    Illuminance Flow Estimation by Regression2010In: International Journal of Computer Vision, ISSN 0920-5691, E-ISSN 1573-1405, Vol. 90, no 3, p. 304-312Article in journal (Refereed)
    Abstract [en]

    We investigate the estimation of illuminance flow using Histograms of Oriented Gradient features (HOGs). In a regression setting, we found for both ridge regression and support vector machines, that the optimal solution shows close resemblance to the gradient based structure tensor (also known as the second moment matrix). Theoretical results are presented showing in detail how the structure tensor and the HOGs are connected. This relation will benefit computer vision tasks such as affine invariant texture/object matching using HOGs. Several properties of HOGs are presented, among others, how many bins are required for a directionality measure, and how to estimate HOGs through spatial averaging that requires no binning.

  • 11.
    Ranftl, Andreas
    et al.
    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.
    Karlsson, Stefan
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
    Face Tracking Using Optical Flow: Development of a Real-Time AdaBoost Cascade Face Tracker2015Conference paper (Refereed)
    Abstract [en]

    In this paper a novel face tracking approach is presented where optical flow information is incorporated into the Viola-Jones face detection algorithm. In the original algorithm from Viola and Jones face detection is static as information from previous frames is not considered. In contrast to the Viola-Jones face detector and also to other known dynamic enhancements, the proposed facetracker preserves information about near-positives. The algorithm builds a likelihood map from the intermediate results of the Viola-Jones algorithm which is extrapolated using optical flow. The objects get extracted from the likelihood map using image segmentation techniques. All steps can be computed very efficiently in real-time. The tracker is verified on the Boston Head Tracking Database showing that the proposed algorithm outperforms the standard Viola-Jones face detector.

  • 12.
    Ranftl, Andreas
    et al.
    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.
    Karlsson, Stefan
    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.
    A Real-Time AdaBoost Cascade Face Tracker Based on Likelihood Map and Optical Flow2017In: IET Biometrics, ISSN 2047-4938, E-ISSN 2047-4946, Vol. 6, no 6, p. 468-477Article in journal (Refereed)
    Abstract [en]

    We present a novel face tracking approach where optical flow information is incorporated into a modified version of the Viola-Jones detection algorithm. In the original algorithm, detection is static, as information from previous frames is not considered; in addition, candidate windows have to pass all stages of the classification cascade, otherwise they are discarded as containing no face. In contrast, the proposed tracker preserves information about the number of classification stages passed by each window. Such information is used to build a likelihood map, which represents the probability of having a face located at that position. Tracking capabilities are provided by extrapolating the position of the likelihood map to the next frame by optical flow computation. The proposed algorithm works in real time on a standard laptop. The system is verified on the Boston Head Tracking Database, showing that the proposed algorithm outperforms the standard Viola-Jones detector in terms of detection rate and stability of the output bounding box, as well as including the capability to deal with occlusions. We also evaluate two recently published face detectors based on Convolutional Networks and Deformable Part Models, with our algorithm showing a comparable accuracy at a fraction of the computation time.

1 - 12 of 12
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