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  • 251.
    Borgefors, G.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Some weighted distance transforms in four dimensions2000Conference paper (Refereed)
    Abstract [en]

    In a digital distance transform, each picture element in the shape (background)

  • 252.
    Borgefors, G.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, I.
    Sanniti di Baja, G.
    Svensson, S.
    Simplification of 3D skeletons using distance information2000Conference paper (Refereed)
    Abstract [en]

    We present a method to simplify the structure of the surface skeleton of a 3D

  • 253.
    Borgefors, G.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Ramella, G.
    Sanniti di Baja, G.
    Hierarchical Decomposition of Multi-Scale Skeletons2001In: IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 23, no 11, p. 1296-1312Article in journal (Refereed)
    Abstract [en]

    This paper presents a new procedure to hierarchically decompose a multi-scale discrete skeleton. The

  • 254.
    Borgefors, G
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Ramella, G
    Sanniti, di Baja G
    Shape and topology preserving multi-valued image pyramids for multi-resolution skeletonization2001In: PATTERN RECOGNITION LETTERS, ISSN 0167-8655, Vol. 22, no 6-7, p. 741-751Article in journal (Refereed)
    Abstract [en]

    Starting from a binary digital image, a multi-valued pyramid is built and suitably treated, so that shape and topology properties of the pattern are preserved satisfactorily at all resolution levels. The multi-valued pyramid can then be used as input data

  • 255.
    Borgefors, G.
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, S.
    Optimal Local Distances for Distance Transforms in 3D using an ExtendedNeighbourhood2001Conference paper (Refereed)
    Abstract [en]

    Digital distance transforms are useful tools for many image analysis tasks. In the

  • 256.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Kedjekod - ett sätt att beskriva former i digitala bilder2005In: Problemlösning är # 1, Liber, Stockholm , 2005, p. 38-42Chapter in book (Other scientific)
  • 257.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Räta linjer på dataskärmen: En illustration av rekursivitet2008In: Nämnaren, ISSN 0348-2723, Vol. 35, no 1, p. 46-50Article in journal (Other (popular science, discussion, etc.))
  • 258.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Tessellationer i matematik, arkitektur och konst2004In: Matenmatikbiennalen 2004: Malmö, 22-24 jan. 2004, 2004, p. 4-Conference paper (Other (popular scientific, debate etc.))
  • 259.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Tessellationer: konsten att dela upp planet i regelbundna mönster2008In: Människor och matematik: Läsebok för nyfikna, Göteborg: NCM , 2008, p. 185-210Chapter in book (Other (popular science, discussion, etc.))
  • 260.
    Borgefors, Gunilla
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    The Scarcity of Universal Colour Names2018In: Proceedings of 7th International Conference on Pattern Recognition Applications and Methods (ICPRAM 2018) / [ed] Maria de Marisco, Gabriella Sannniti di Baja, Ana Fred, SciTePress, 2018, p. 496-502Conference paper (Refereed)
    Abstract [en]

    There is a trend in Computer Vision to use over twenty colour names for image annotation, retrieval and to train deep learning networks to name unknown colours for human use. This paper will show that there is little consistency of colour naming between languages and even between individuals speaking the same language. Experiments will be cited that show that your mother tongue influences how your brain processes colour. It will also be pointed out that the eleven so called basic colours in English are not universal and cannot be applied to other languages. The conclusion is that only the six Hering primary colours, possibly with simple qualifications, are the only ones you should use if you aim for universal usage of your systems. That is: black, white, red, green, blue, and yellow.

  • 261.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Weighted digital distance transforms in four dimensions2003In: Discrete Applied Mathematics, Vol. 125, p. 161-176Article in journal (Refereed)
    Abstract [en]

    A digital distance transformation converts a binary image in Z^n to a distance transform, where each picture element in the foreground (background) has a value measuring the closest distance to the background (foreground). In a weighted distance transform

  • 262.
    Borgefors, Gunilla
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Weighted distance transforms in four dimensions2003In: Discrete Applied Mathematics, Vol. 125, p. 161-176Article in journal (Refereed)
    Abstract [en]

    A digital distance transformation converts a binary image in Z^n to a distance transform, where each picture element in the foreground (background) has a value measuring the closest distance to the background (foreground). In a weighted distance transform

  • 263.
    Borgefors, Gunilla
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Nyström, Ingela
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Sanniti di Baja, Gabriella
    Institute of Cybernetics ``E. Caianiello," C.N.R., Pozzuoli, Naples,.
    Discrete Skeletons from Distance Transforms in 2D and 3D2008In: Medial Representations: Mathematics, Algorithms and Applications, Netherlands: Springer Verlag , 2008, p. 155-190Chapter in book (Other academic)
    Abstract [en]

    We present discrete methods to compute the digital skeleton of shapes in 2D and 3D images. In 2D, the skeleton is a set of curves, while in 3D it will be a set of surfaces and curves, the surface skeleton, or a set of curves, the curve skeleton. A general scheme could, in principle, be followed for both 2D and 3D discrete skeletonization. However, we will describe one approach for 2D skeletonization, mainly based on marking in the distance transform the shape elements that should be assigned to the skeleton, and another approach for 3D skeletonization, mainly based on iterated element removal. In both cases, the distance transform of the image will play a key role to obtain skeletons reflecting important shape features such as symmetry, elongation, and width.

  • 264.
    Borgefors, Gunilla
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    An Approximation of the Maximal Inscribed Convex Set of a Digital Obj2005In: In F. Roli and S. Vitulano, editors, Proceedings of 13th International Conference on Image Analysis and Processing (ICIAP'05), 2005, p. 438-445Conference paper (Refereed)
    Abstract [en]

    In several application projects we have discovered the need of computing the maximal inscribed convex set of a digital shape. Here we present an algorithm for computing a reasonable approximation of this set, that can be used in both 2D and 3D. The main idea is to iteratively identify the deepest concavity and then remove it by cutting off as little as possible of the shape. We show results using both synthetic and real examples.

  • 265.
    Borgefors, Gunilla
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    On Maximal Balls in Three Volume Grids2009In: PRIP'2009: Pattern Recognition and Information Processing, Minsk, Belarus, Minsk: Publishing Center of BSU , 2009, p. 31-36Conference paper (Refereed)
    Abstract [en]

    A volume image can be digitized in different grids, not only the cubic one. The fcc and bcc grids have many advantages, as they are more dense than the cubic one. The set of maximal balls in a shape in a volume image is a compact but complete description of the shape. The original set, identified by rules dependent on the metric used, can be further reduced, by observing that some balls are covered by groups of other balls. The set of maximal balls can, for example, be used for compression, manipulation and as anchor points for topologically correct medial representations.

  • 266.
    Borgefors, Gunilla
    et al.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Svensson, Stina
    Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Fuzzy border distance transforms and their use in 2D skeletonization2002Conference paper (Refereed)
    Abstract [en]

    Segmentation is always a difficult task in image analysis. In this paper,

  • 267. Borodulina, Svetlana
    et al.
    Wernersson, Erik L. G.
    Kulachenko, Artem
    Luengo Hendriks, Cris L.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Extracting fiber and network connectivity data using microtomography images of paper2016In: Nordic Pulp & Paper Research Journal, ISSN 0283-2631, E-ISSN 2000-0669, Vol. 31, no 3, p. 469-478Article in journal (Refereed)
  • 268.
    Boström, Henrik
    University of Skövde, School of Humanities and Informatics. University of Skövde, The Informatics Research Centre.
    Maximizing the Area under the ROC Curve with Decision Lists and Rule Sets2007In: Proceedings of the 7th SIAM International Conference on Data Mining / [ed] C. Apte, B. Liu, S. Parthasarathy, D. Skillicorn, Society for Industrial and Applied Mathematics , 2007, p. 27-34Conference paper (Refereed)
    Abstract [en]

    Decision lists (or ordered rule sets) have two attractive properties compared to unordered rule sets: they require a simpler classi¯cation procedure and they allow for a more compact representation. However, it is an open question what effect these properties have on the area under the ROC curve (AUC). Two ways of forming decision lists are considered in this study: by generating a sequence of rules, with a default rule for one of the classes, and by imposing an order upon rules that have been generated for all classes. An empirical investigation shows that the latter method gives a significantly higher AUC than the former, demonstrating that the compactness obtained by using one of the classes as a default is indeed associated with a cost. Furthermore, by using all applicable rules rather than the first in an ordered set, an even further significant improvement in AUC is obtained, demonstrating that the simple classification procedure is also associated with a cost. The observed gains in AUC for unordered rule sets compared to decision lists can be explained by that learning rules for all classes as well as combining multiple rules allow for examples to be ranked according to a more fine-grained scale compared to when applying rules in a fixed order and providing a default rule for one of the classes.

  • 269.
    Bouhennache, Rafik
    et al.
    Science and technology institute, university center of Mila, DZA.
    Bouden, Toufik
    ohammed Seddik Ben Yahia University of Jijel, DZA.
    Taleb-Ahmed, Abdmalik
    university of V alenciennes, FRA.
    Cheddad, Abbas
    Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering. Blekinge Institute of Technology.
    A new spectral index for the extraction of built-up land features from Landsat 8 satellite imagery2019In: Geocarto International, ISSN 1010-6049, E-ISSN 1752-0762, Vol. 34, no 14, p. 1531-1551Article in journal (Refereed)
    Abstract [en]

    Extracting built-up areas from remote sensing data like Landsat 8 satellite is a challenge. We have investigated it by proposing a new index referred as Built-up Land Features Extraction Index (BLFEI). The BLFEI index takes advantage of its simplicity and good separability between the four major component of urban system, namely built-up, barren, vegetation and water. The histogram overlap method and the Spectral Discrimination Index (SDI) are used to study separability. BLFEI index uses the two bands of infrared shortwaves, the red and green bands of the visible spectrum. OLI imagery of Algiers, Algeria, was used to extract built-up areas through BLFEI and some new previously developed built-up indices used for comparison. The water areas are masked out leading to Otsu’s thresholding algorithm to automatically find the optimal value for extracting built-up land from waterless regions. BLFEI, the new index improved the separability by 25% and the accuracy by 5%.

  • 270.
    Boyer, E
    et al.
    Grenoble, France.
    Bronstein, A.M.
    Tel Aviv University, Israel.
    Bronstein, M.M.
    Università della Svizzera Italiana, Lugano, Switzerland.
    Bustos, B
    University of Chile.
    Darom, T
    Bar-Ilan University, Ramat-Gan, Israel.
    Horaud, R
    Grenoble, France.
    Hotz, Ingrid
    Zuse Institue Berlin.
    Kelle, Y
    Bar-Ilan University, Ramat-Gan, Israel.
    Keustermans, J
    K.U. Leuven, Belgium.
    Kovnatsky, A
    Israel Institute of Technology, Haifa, Israel.
    Litman, R
    Tel Aviv University, Israel.
    Reininghaus, Jan
    Zuse Institue Berlin.
    Sipiran, I
    University of Chile.
    Smeets, D
    K.U. Leuven, Belgium.
    Suetens, P
    K.U. Leuven, Belgium.
    Vandermeulen, D
    K.U. Leuven, Belgium.
    Zaharescu, A
    Waterloo, Canada.
    Zobel, Valentin
    Zuse Institut Berlin, Germany.
    SHREC 2011: Robust Feature Detection and Description Benchmark2011Conference paper (Refereed)
    Abstract [en]

    Feature-based approaches have recently become very popular in computer vision and image analysis applications, and are becoming a promising direction in shape retrieval. SHREC’11 robust feature detection and description benchmark simulates the feature detection and description stages of feature-based shape retrieval algorithms. The benchmark tests the performance of shape feature detectors and descriptors under a wide variety of transformations. The benchmark allows evaluating how algorithms cope with certain classes of transformations and strength of the transformations that can be dealt with. The present paper is a report of the SHREC’11 robust feature detection and description benchmark results.

  • 271.
    Bradler, Henry
    et al.
    Goethe University of Frankfurt, Germany.
    Anne Wiegand, Birthe
    Goethe University of Frankfurt, Germany.
    Mester, Rudolf
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Goethe University of Frankfurt, Germany.
    The Statistics of Driving Sequences - and what we can learn from them2015In: 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION WORKSHOP (ICCVW), IEEE , 2015, p. 106-114Conference paper (Refereed)
    Abstract [en]

    The motion of a driving car is highly constrained and we claim that powerful predictors can be built that learn the typical egomotion statistics, and support the typical tasks of feature matching, tracking, and egomotion estimation. We analyze the statistics of the ground truth data given in the KITTI odometry benchmark sequences and confirm that a coordinated turn motion model, overlaid by moderate vibrations, is a very realistic model. We develop a predictor that is able to significantly reduce the uncertainty about the relative motion when a new image frame comes in. Such predictors can be used to steer the matching process from frame n to frame n + 1. We show that they can also be employed to detect outliers in the temporal sequence of egomotion parameters.

  • 272.
    Bradler, Henry
    et al.
    Goethe University, Germany.
    Ochs, Matthias
    Goethe University, Germany.
    Fanani, Nolang
    Goethe University, Germany.
    Mester, Rudolf
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Goethe University, Germany.
    Joint Epipolar Tracking (JET): Simultaneous optimization of epipolar geometry and feature correspondences2017In: 2017 IEEE WINTER CONFERENCE ON APPLICATIONS OF COMPUTER VISION (WACV 2017), IEEE , 2017, p. 445-453Conference paper (Refereed)
    Abstract [en]

    Traditionally, pose estimation is considered as a two step problem. First, feature correspondences are determined by direct comparison of image patches, or by associating feature descriptors. In a second step, the relative pose and the coordinates of corresponding points are estimated, most often by minimizing the reprojection error (RPE). RPE optimization is based on a loss function that is merely aware of the feature pixel positions but not of the underlying image intensities. In this paper, we propose a sparse direct method which introduces a loss function that allows to simultaneously optimize the unscaled relative pose, as well as the set of feature correspondences directly considering the image intensity values. Furthermore, we show how to integrate statistical prior information on the motion into the optimization process. This constructive inclusion of a Bayesian bias term is particularly efficient in application cases with a strongly predictable (short term) dynamic, e.g. in a driving scenario. In our experiments, we demonstrate that the JET` algorithm we propose outperforms the classical reprojection error optimization on two synthetic datasets and on the KITTI dataset. The JET algorithm runs in real-time on a single CPU thread.

  • 273.
    Brandl, Miriam B
    et al.
    School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia .
    Beck, Dominik
    School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia .
    Pham, Tuan D
    School of Engineering and Information Technology, The University of New South Wales, Canberra, Australia .
    Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of Breast Cancer2011Conference paper (Refereed)
    Abstract [en]

    The high dimensionality of image‐based dataset can be a drawback for classification accuracy. In this study, we propose the application of fuzzy c‐means clustering, cluster validity indices and the notation of a joint‐feature‐clustering matrix to find redundancies of image‐features. The introduced matrix indicates how frequently features are grouped in a mutual cluster. The resulting information can be used to find data‐derived feature prototypes with a common biological meaning, reduce data storage as well as computation times and improve the classification accuracy

  • 274.
    Brandtberg, T.
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Individual tree-based timber volume assessment using high spatial resolution laserscanning data2000In: Symposium on Image Analysis - SSAB 2000, 2000, p. 83-86Conference paper (Other scientific)
  • 275.
    Brandtberg, Tomas
    Uppsala University, Interfaculty Units, Centre for Image Analysis. Teknisk-naturvetenskapliga vetenskapsområdet, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Individual Tree-based Species Classification in High Spatial Resolution Aerial Images of Forests using Fuzzy Sets2002In: Fuzzy Sets and Systems, Vol. 132, no 3, p. 371-387Article in journal (Refereed)
    Abstract [en]

    This paper presents an application of fuzzy set theory for classification of individual tree crowns into species groups, in high

  • 276.
    Brandtberg, Tomas
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Saab Dynam AB, Linköping, Sweden.
    Virtual hexagonal and multi-scale operator for fuzzy rank order texture classification using one-dimensional generalised Fourier analysis2016In: 2016 23RD INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR), IEEE COMPUTER SOC , 2016, p. 2018-2024Conference paper (Refereed)
    Abstract [en]

    This paper presents a study on a family of local hexagonal and multi-scale operators useful for texture analysis. The hexagonal grid shows an attractive rotation symmetry with uniform neighbour distances. The operator depicts a closed connected curve (1D periodic). It is resized within a scale interval during the conversion from the original square grid to the virtual hexagonal grid. Complementary image features, together with their tangential first-order hexagonal derivatives, are calculated. The magnitude/phase information from the Fourier or Fractional Fourier Transform (FFT, FrFT) are accumulated in thirty different Cartesian (polar for visualisation) and multi-scale domains. Simultaneous phase-correlation of a subset of the data gives an estimate of scaling/rotation relative the references. Similarity metrics are used as template matching. The sample, unseen by the system, is classified into the group with the maximum fuzzy rank order. An instantiation of a 12-point hexagonal operator (radius=2) is first successfully evaluated on a set of thirteen Brodatz images (no scaling/rotation). Then it is evaluated on the more challenging KTH-TIPS2b texture dataset (scaling/rotation, varying pose/illumination). A confusion matrix and cumulative fuzzy rank order summaries show, for example, that the correct class is top-ranked 44 - 50% and top-three ranked 68 - 76% of all sample images. A similar evaluation, using a box-like 12-point mask of square grids, gives overall lower accuracies. Finally, the FrFT parameter is an additional tuning parameter influencing the accuracies significantly.

  • 277.
    Brattberg, Oskar
    et al.
    Dept. of IR Systems, Div. of Sensor Tecnology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Ahlberg, Jörgen
    Dept. of IR Systems, Div. of Sensor Tecnology, Swedish Defence Research Agency (FOI), Linköping, Sweden.
    Analysis of Multispectral Reconnaissance Imagery for Target Detection and Operator Support2006Conference paper (Other academic)
    Abstract [en]

    This paper describes a method to estimate motion in an image sequence acquired using a multispectral airborne sensor. The purpose of the motion estimation is to align the sequentually acquired spectral bands and fuse them into multispectral images. These multispectral images are then analysed and presented in order to support an operator in an air-to-ground reconnaissance scenario.

  • 278.
    Bremer, Peer-Timo
    et al.
    California, Usa.
    Hotz, IngridBerlin, Germany.Pascucci, ValerioUtah, Usa.Peikert, RonaldZurich, Switzerland.
    Topological Methods in Data Analysis and Visualization III: Theory, Algorithms, and Applications2014Collection (editor) (Refereed)
  • 279.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Laptev, Ivan
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Hand-gesture recognition using multi-scale colour features, hierarchical features and particle filtering2002In: Fifth IEEE International Conference on Automatic Face and Gesture Recognition, 2002. Proceedings, IEEE conference proceedings, 2002, p. 63-74Conference paper (Refereed)
    Abstract [en]

    This paper presents algorithms and a prototype systemfor hand tracking and hand posture recognition. Hand posturesare represented in terms of hierarchies of multi-scalecolour image features at different scales, with qualitativeinter-relations in terms of scale, position and orientation. Ineach image, detection of multi-scale colour features is performed.Hand states are then simultaneously detected andtracked using particle filtering, with an extension of layeredsampling referred to as hierarchical layered sampling. Experimentsare presented showing that the performance ofthe system is substantially improved by performing featuredetection in colour space and including a prior with respectto skin colour. These components have been integrated intoa real-time prototype system, applied to a test problem ofcontrolling consumer electronics using hand gestures. In asimplified demo scenario, this system has been successfullytested by participants at two fairs during 2001.

  • 280.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Laptev, Ivan
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Lenman, S.
    Sundblad, Y.
    A Prototype System for Computer Vision Based Human Computer Interaction2001Report (Other academic)
  • 281.
    Bretzner, Lars
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Lindeberg, Tony
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Feature Tracking with Automatic Selection of Spatial Scales1998In: Computer Vision and Image Understanding, ISSN 1077-3142, E-ISSN 1090-235X, Vol. 71, no 3, p. 385-393Article in journal (Refereed)
    Abstract [en]

    When observing a dynamic world, the size of image structures may vary over time. This article emphasizes the need for including explicit mechanisms for automatic scale selection in feature tracking algorithms in order to: (i) adapt the local scale of processing to the local image structure, and (ii) adapt to the size variations that may occur over time. The problems of corner detection and blob detection are treated in detail, and a combined framework for feature tracking is presented. The integrated tracking algorithm overcomes some of the inherent limitations of exposing fixed-scale tracking methods to image sequences in which the size variations are large. It is also shown how the stability over time of scale descriptors can be used as a part of a multi-cue similarity measure for matching. Experiments on real-world sequences are presented showing the performance of the algorithm when applied to (individual) tracking of corners and blobs.

  • 282.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Feature tracking with automatic selection of spatial scales1998Report (Other academic)
    Abstract [en]

    When observing a dynamic world, the size of image structures may vary over nada. This article emphasizes the need for including explicit mechanisms for automatic scale selection in feature tracking algorithms in order to: (i) adapt the local scale of processing to the local image structure, and (ii) adapt to the size variations that may occur over time.

    The problems of corner detection and blob detection are treated in detail, and a combined framework for feature tracking is presented in which the image features at every time moment are detected at locally determined and automatically selected nadaes. A useful property of the scale selection method is that the scale levels selected in the feature detection step reflect the spatial extent of the image structures. Thereby, the integrated tracking algorithm has the ability to adapt to spatial as well as temporal size variations, and can in this way overcome some of the inherent limitations of exposing fixed-scale tracking methods to image sequences in which the size variations are large.

    In the composed tracking procedure, the scale information is used for two additional major purposes: (i) for defining local regions of interest for searching for matching candidates as well as setting the window size for correlation when evaluating matching candidates, and (ii) stability over time of the scale and significance descriptors produced by the scale selection procedure are used for formulating a multi-cue similarity measure for matching.

    Experiments on real-world sequences are presented showing the performance of the algorithm when applied to (individual) tracking of corners and blobs. Specifically, comparisons with fixed-scale tracking methods are included as well as illustrations of the increase in performance obtained by using multiple cues in the feature matching step.

  • 283.
    Bretzner, Lars
    et al.
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
    Lindeberg, Tony
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    On the handling of spatial and temporal scales in feature tracking1997In: Scale-Space Theory in Computer Vision: First International Conference, Scale-Space'97 Utrecht, The Netherlands, July 2–4, 1997 Proceedings, Springer Berlin/Heidelberg, 1997, p. 128-139Conference paper (Refereed)
  • 284.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Qualitative Multi-Scale Feature Hierarchies for Object Tracking2000In: Journal of Visual Communication and Image Representation, ISSN 1047-3203, E-ISSN 1095-9076, Vol. 11, p. 115-129Article in journal (Refereed)
    Abstract [en]

    This paper shows how the performance of feature trackers can be improved by building a view-based object representation consisting of qualitative relations between image structures at different scales. The idea is to track all image features individually, and to use the qualitative feature relations for resolving ambiguous matches and for introducing feature hypotheses whenever image features are mismatched or lost. Compared to more traditional work on view-based object tracking, this methodology has the ability to handle semi-rigid objects and partial occlusions. Compared to trackers based on three-dimensional object models, this approach is much simpler and of a more generic nature. A hands-on example is presented showing how an integrated application system can be constructed from conceptually very simple operations.

  • 285.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Qualitative multiscale feature hierarchies for object tracking2000Report (Refereed)
    Abstract [en]

    This paper shows how the performance of feature trackers can be improved by building a hierarchical view-based object representation consisting of qualitative relations between image structures at different scales. The idea is to track all image features individually and to use the qualitative feature relations for avoiding mismatches, for resolving ambiguous matches, and for introducing feature hypotheses whenever image features are lost. Compared to more traditional work on view-based object tracking, this methodology has the ability to handle semirigid objects and partial occlusions. Compared to trackers based on three-dimensional object models, this approach is much simpler and of a more generic nature. A hands-on example is presented showing how an integrated application system can be constructed from conceptually very simple operations.

  • 286.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
    Qualitative multi-scale feature hierarchies for object tracking1999In: Proc Scale-Space Theories in Computer Vision Med, Elsevier, 1999, p. 117-128Conference paper (Refereed)
    Abstract [en]

    This paper shows how the performance of feature trackers can be improved by building a view-based object representation consisting of qualitative relations between image structures at different scales. The idea is to track all image features individually, and to use the qualitative feature relations for resolving ambiguous matches and for introducing feature hypotheses whenever image features are mismatched or lost. Compared to more traditional work on view-based object tracking, this methodology has the ability to handle semi-rigid objects and partial occlusions. Compared to trackers based on three-dimensional object models, this approach is much simpler and of a more generic nature. A hands-on example is presented showing how an integrated application system can be constructed from conceptually very simple operations.

  • 287.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Structure and Motion Estimation using Sparse Point and Line Correspondences in Multiple Affine Views1999Report (Other academic)
    Abstract [en]

    This paper addresses the problem of computing three-dimen\-sional structure and motion from an unknown rigid configuration of points and lines viewed by an affine projection model. An algebraic structure, analogous to the trilinear tensor for three perspective cameras, is defined for configurations of three centered affine cameras. This centered affine trifocal tensor contains 12 non-zero coefficients and involves linear relations between point correspondences and trilinear relations between line correspondences. It is shown how the affine trifocal tensor relates to the perspective trilinear tensor, and how three-dimensional motion can be computed from this tensor in a straightforward manner. A factorization approach is developed to handle point features and line features simultaneously in image sequences, and degenerate feature configurations are analysed. This theory is applied to a specific problem in human-computer interaction of capturing three-dimensional rotations from gestures of a human hand. This application to quantitative gesture analyses illustrates the usefulness of the affine trifocal tensor in a situation where sufficient information is not available to compute the perspective trilinear tensor, while the geometry requires point correspondences as well as line correspondences over at least three views.

  • 288.
    Bretzner, Lars
    et al.
    KTH, Superseded Departments, Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    Use your hand as a 3-D mouse or relative orientation from extended sequences of sparse point and line correspondances using the affine trifocal tensor1998In: Computer Vision — ECCV'98: 5th European Conference on Computer Vision Freiburg, Germany, June, 2–6, 1998 Proceedings, Volume I, Springer Berlin/Heidelberg, 1998, Vol. 1406, p. 141-157Conference paper (Refereed)
    Abstract [en]

    This paper addresses the problem of computing three-dimensional structure and motion from an unknown rigid configuration of point and lines viewed by an affine projection model. An algebraic structure, analogous to the trilinear tensor for three perspective cameras, is defined for configurations of three centered affine cameras. This centered affine trifocal tensor contains 12 coefficients and involves linear relations between point correspondences and trilinear relations between line correspondences It is shown how the affine trifocal tensor relates to the perspective trilinear tensor, and how three-dimensional motion can be computed from this tensor in a straightforward manner. A factorization approach is also developed to handle point features and line features simultaneously in image sequences.

    This theory is applied to a specific problem of human-computer interaction of capturing three-dimensional rotations from gestures of a human hand. A qualitative model is presented, in which three fingers are represented by their position and orientation, and it is shown how three point correspondences (blobs at the finger tips) and three line correspondences (ridge features at the fingers) allow the affine trifocal tensor to be determined, from which the rotation is computed. Besides the obvious application, this test problem illustrates the usefulness of the affine trifocal tensor in a situation where sufficient information is not available to compute the perspective trilinear tensor, while the geometry requires point correspondences as well as line correspondences over at least three views.

  • 289. Bricault, Ivan
    et al.
    Zemiti, Nabil
    Jouniaux, Emilie
    Fouard, Celine
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Taillant, Elise
    Dorandeu, Frederic
    Cinquin, Philippe
    A light puncture robot for CT and MRI interventions2008In: IEEE Engineering in Medicine and Biology Magazine, ISSN 0739-5175, E-ISSN 1937-4186, Vol. 27, no 3, p. 42-50Article in journal (Refereed)
  • 290.
    Broberg, Patrik
    University West, Department of Engineering Science, Division of Process and Product Development.
    Towards Automation of Non-Destructive Testing of Welds2011Licentiate thesis, comprehensive summary (Other academic)
    Abstract [en]

    All welding processes can give rise to defects that will weaken the joint and can lead to failure of the welded structure. Because of this, non-destructive testing (NDT) of welds have become increasingly important to ensure the structural integrity when the material becomes thinner and stronger and welds become smaller; all to reduce weight in order to save material and reduce emissions due to lighter constructions.

    Several NDT methods exists for testing welds and they all have their advantages and disadvantages when it comes to the types and sizes of defects that are detectable, but also in the ability to automate the method. Several methods were compared using common weld defects to determine which method or methods were best suited for automated NDT of welds. The methods compared were radiography, phased array ultrasound, eddy current, thermography and shearography. Phased array ultrasound was deemed most suitable for detecting the weld defects used in the comparison and for automation and was therefore chosen to be used in the continuation of this work. Thermography was shown to be useful for detecting surface defects; something not easily detected using ultrasound. A combination of these techniques will be able to find most weld defects of interest.

    Automation of NDT can be split into two separate areas; mechanisation of the testing and automation of the analysis, both presenting their own difficulties. The problem of mechanising the testing has been solved for simple geometries but for more general welds it will require a more advance system using an industrial robot or similar. Automation of the analysis of phased array ultrasound data consists of detection, sizing, positioning and classification of defects. There are several problems to solve before a completely automatic analysis can be made, including positioning of the data, improving signal quality, segmenting the images and classifying the defects. As a step on the way towards positioning of the data, and thereby easing the analysis, the phase of the signal was studied. It was shown that the phase can be used for finding corners in the image and will also improve the ability to position the corner as compared to using the amplitude of the signal. Further work will have to be done to improve the signal in order to reliably analyse the data automatically.

  • 291.
    Brolund, Hans
    Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
    Förbättring av fluoroskopibilder2006Independent thesis Basic level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In X-ray technology, fluoroscopy stands for continuous irradiation. For the sake of both patients and doctors the dose has to be kept low, which leads to noisy images and the question of possible enhancement by digital image processing. Since such enhancement has to be done in real-time, most conventional and available methods are unsuitable.

    The purpose of this thesis is to examine how derivative operators can be used to improve fluoroscopy images in terms of noise reduction and edge enhancement. Since the derivative operators are designed as highly separable convolution kernels the image derivatives can be computed very efficiently with a scheme that is readily embedded in a scale-space pyramid. In this pyramid, structures and details of different sizes can be processed separately with optimal parameter settings. In the final solution we also discriminate between structure and noise in order to avoid amplification, even suppress contributions from frequency bands where a certain pixel position is dominated by noise.

    Experimental results show that noise can indeed be suppressed while edges and lines are enhanced. Oriented filtering may induce false structures in areas where only noise is present, something that can be avoided by correcting the parameters in the noise/structure discriminator. The relation between oriented and non-oriented filtering is likewise controllable with a parameter that can be optimized for application dependent needs and desires.

  • 292.
    Brolund, Per
    Linköping University, Department of Electrical Engineering.
    Forensisk längdmätning i bilder2006Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
    Abstract [sv]

    Detta examensarbete undersöker forensisk längdmätning i bild, t ex längduppskattning av människor i bilder rörande brottsmål. Problemen identifieras och några av dagens befintliga längdmätningsmetoder diskuteras.

    Den metod som bäst uppfyller de i arbetet ställda kraven, d v s snabb handläggning, minimal systeminformation, minimalt arbete på plats och exakthet, har valts ut, anpassats och utvärderats. Metoden bygger på att hitta s k gränspunkter och grundplanets gränslinje i bilden och utifrån en i världen känd referenslängd beräkna den sökta längden. Den bakomliggande teorin presenteras och metoden beskrivs i detalj. Funktioner, algoritmer och ett användargränssnitt har implementerats i beräkningsprogrammet MatLab. Tester har utförts för att validera metodens noggrannhet och parameterberoende. Metoden visar sig ge mycket bra resultat då rätt förutsättningar ges, men har konstaterats vara känslig för variation på gränslinjen. En rad förbättringsförslag presenteras för att utveckla metoden och stabilisera resultatet.

    Examensarbetet omfattar 20 högskolepoäng och utgör ett obligatoriskt moment i utbildningsprogrammet civilingenjör i datateknik som ges av Linköpings universitet. Arbetet är utfört vid och på uppdrag av Statens kriminaltekniska laboratorium (SKL) i Linköping.

  • 293.
    Brorson, Erik
    Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
    Classifying Hate Speech using Fine-tuned Language Models2018Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Given the explosion in the size of social media, the amount of hate speech is also growing. To efficiently combat this issue we need reliable and scalable machine learning models. Current solutions rely on crowdsourced datasets that are limited in size, or using training data from self-identified hateful communities, that lacks specificity. In this thesis we introduce a novel semi-supervised modelling strategy. It is first trained on the freely available data from the hateful communities and then fine-tuned to classify hateful tweets from crowdsourced annotated datasets. We show that our model reach state of the art performance with minimal hyper-parameter tuning.

  • 294.
    Brucker, Manuel
    et al.
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany..
    Durner, Maximilian
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany..
    Ambrus, Rares
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Marton, Zoltan Csaba
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany..
    Wendt, Axel
    Robert Bosch, Corp Res, St Joseph, MI USA.;Robert Bosch, Corp Res, Gerlingen, Germany..
    Jensfelt, Patric
    KTH, School of Electrical Engineering and Computer Science (EECS), Robotics, perception and learning, RPL. KTH, School of Electrical Engineering and Computer Science (EECS), Centres, Centre for Autonomous Systems, CAS.
    Arras, Kai O.
    Robert Bosch, Corp Res, St Joseph, MI USA.;Robert Bosch, Corp Res, Gerlingen, Germany..
    Triebel, Rudolph
    German Aerosp Ctr DLR, Inst Robot & Mechatron, D-82234 Oberpfaffenhofen, Germany.;Tech Univ Munich, Dep Comp Sci, Munich, Germany..
    Semantic Labeling of Indoor Environments from 3D RGB Maps2018In: 2018 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), IEEE Computer Society, 2018, p. 1871-1878Conference paper (Refereed)
    Abstract [en]

    We present an approach to automatically assign semantic labels to rooms reconstructed from 3D RGB maps of apartments. Evidence for the room types is generated using state-of-the-art deep-learning techniques for scene classification and object detection based on automatically generated virtual RGB views, as well as from a geometric analysis of the map's 3D structure. The evidence is merged in a conditional random field, using statistics mined from different datasets of indoor environments. We evaluate our approach qualitatively and quantitatively and compare it to related methods.

  • 295.
    Brun, Anders
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Extending Distance Computation - Propagating Derivatives2010In: Proceedings SSBA 2010 / [ed] Cris Luengo and Milan Gavrilovic, Uppsala: Centre for Image Analysis , 2010, p. 39-42Conference paper (Other academic)
    Abstract [en]

    In this paper we present a technique to extend distance computation  algorithms that compute global distances from a series of local  updates. This includes algorithms such as the fast marching method  (FMM) and the chamfering algorithm for weighted distances. In  addition to the value of a distance function or distance map, we  derive formulas to compute the gradient and higher order partial  derivatives of the distance function within the same framework. The  approach is based on symbolic differentiation of the update scheme,  which makes it general and straight forward to apply to almost any  distance computation scheme. The main result is a novel set of  ``derivative maps'' that are computed along with the ordinary  distance maps. Apart from the theory itself, these maps and this  technique may be used to compute skeletons and parameterizations  such as Riemannian Normal Coordinates and Gauss Normal Coordinates.

  • 296.
    Brun, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Knutsson, Hans
    Department of Medical Engineering, Linköpings Universitet.
    Geodesic Glyph Warping2008In: Proceedings of SSBA, Lund, Sweden: SSBA , 2008Conference paper (Other academic)
  • 297.
    Brun, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Knutsson, Hans
    Linköpings Universitet.
    Tensor Glyph Warping: Visualizing Metric Tensor Fields using Riemannian Exponential Maps2009In: Visualization and Processing of Tensor Fields: Advances and Perspectives / [ed] David Laidlaw, Joachim Weickert, Berlin Heidelberg: Springer , 2009, XVII, p. 139-160Chapter in book (Other academic)
    Abstract [en]

    The Riemannian exponential map, and its inverse the Riemannian logarithm map, can be used to visualize metric tensor fields. In this chapter we first derive the well-known metric sphere glyph from the geodesic equation, where the tensor field to be visualized is regarded as the metric of a manifold. These glyphs capture the appearance of the tensors relative to the coordinate system of the human observer. We then introduce two new concepts for metric tensor field visualization: geodesic spheres and geodesically warped glyphs. These extensions make it possible not only to visualize tensor anisotropy, but also the curvature and change in tensor-shape in a local neighborhood. The framework is based on the exp p (v i ) and log p (q) maps, which can be computed by solving a second-order ordinary differential equation (ODE) or by manipulating the geodesic distance function. The latter can be found by solving the eikonal equation, a nonlinear partial differential equation (PDE), or it can be derived analytically for some manifolds. To avoid heavy calculations, we also include first- and second-order Taylor approximations to exp and log. In our experiments, these are shown to be sufficiently accurate to produce glyphs that visually characterize anisotropy, curvature, and shape-derivatives in sufficiently smooth tensor fields where most glyphs are relatively similar in size.

  • 298.
    Brun, Anders
    et al.
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Centre for Image Analysis, SLU, Uppsala, Sweden.
    Martin-Fernandez, Marcos
    Universidad de Valladolid Laboratorio de Procesado de Imagen (LPI), Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática Spain.
    Acar, Burac
    Boğaziçi University 5 Electrical & Electronics Engineering Department Istanbul Turkey.
    Munoz-Moreno, Emma
    Universidad de Valladolid Laboratorio de Procesado de Imagen (LPI), Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática Spain.
    Cammoun, Leila
    Signal Processing Institute (ITS), Ecole Polytechnique Fédérale Lausanne (EPFL) Lausanne Switzerland.
    Sigfridsson, Andreas
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Center for Technology in Medicine, Dept. Señales y Comunicaciones, University of Las Palmas de Gran Canaria, Spain.
    Sosa-Cabrera, Dario
    Center for Technology in Medicine, Dept. Señales y Comunicaciones, University of Las Palmas de Gran Canaria, Spain.
    Svensson, Björn
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Herberthson, Magnus
    Linköping University, Department of Mathematics, Applied Mathematics. Linköping University, The Institute of Technology.
    Knutsson, Hans
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Similar Tensor Arrays - A Framework for Storage of Tensor Array Data2009In: Tensors in Image Processing and Computer Vision / [ed] Santiago Aja-Fern´andez, Rodrigo de Luis Garc´ıa, Dacheng Tao, Xuelong Li, Springer Science+Business Media B.V., 2009, 1, p. 407-428Chapter in book (Refereed)
    Abstract [en]

    This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.

  • 299.
    Brun, Anders
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Centre for Image Analysis.
    Martin-Fernandez, Marcos
    Dept. Teoría de la Señal y Comunicaciones e Ingeniería Telemática, Universidad de Valladolid, Spain.
    Acar, Burak
    Munoz-Moreno, Emma
    Cammoun, Leila
    Signal Processing Institute (ITS), Ecole Polytechnique Fédérale Lausanne (EPFL), Lausanne, Switzerland.
    Sigfridsson, Andreas
    Division of Medical Informatics, Department of Biomedical Engineering, Linköping University, Linköping, Spain.
    Sosa-Cabrera, Dario
    Center for Technology in Medicine, Dept. Señales y Comunicaciones, University of Las Palmas de Gran Canaria, Spain.
    Svensson, jörn
    Dept. of biomedical Engineering, Linköpings Universitet.
    Herberthson, Magnus
    Dept. of mathematics, linköpings universitet.
    Knutsson, Hans
    Dept of biomedical engineering, Linköpings universitet.
    Similar Tensor Arrays: A Framework for Storage of Tensor Array Data2009In: Tensors in Image Processing and Computer Vision, London: Springer , 2009, 1, p. 407-428Chapter in book (Other academic)
    Abstract [en]

    Abstract This chapter describes a framework for storage of tensor array data, useful to describe regularly sampled tensor fields. The main component of the framework, called Similar Tensor Array Core (STAC), is the result of a collaboration between research groups within the SIMILAR network of excellence. It aims to capture the essence of regularly sampled tensor fields using a minimal set of attributes and can therefore be used as a “greatest common divisor” and interface between tensor array processing algorithms. This is potentially useful in applied fields like medical image analysis, in particular in Diffusion Tensor MRI, where misinterpretation of tensor array data is a common source of errors. By promoting a strictly geometric perspective on tensor arrays, with a close resemblance to the terminology used in differential geometry, (STAC) removes ambiguities and guides the user to define all necessary information. In contrast to existing tensor array file formats, it is minimalistic and based on an intrinsic and geometric interpretation of the array itself, without references to other coordinate systems.

  • 300.
    Brunnström, Kjell
    et al.
    KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
    Eklundh, Jan-Olof
    KTH, Superseded Departments (pre-2005), Numerical Analysis and Computer Science, NADA.
    Lindeberg, Tony
    KTH, School of Computer Science and Communication (CSC), Computational Biology, CB.
    On Scale and Resolution in the Analysis of Local Image Structure1990In: Proc. 1st European Conf. on Computer Vision, 1990, Vol. 427, p. 3-12Conference paper (Refereed)
    Abstract [en]

    Focus-of-attention is extremely important in human visual perception. If computer vision systems are to perform tasks in a complex, dynamic world they will have to be able to control processing in a way that is analogous to visual attention in humans.

    In this paper we will investigate problems in connection with foveation, that is examining selected regions of the world at high resolution. We will especially consider the problem of finding and classifying junctions from this aspect. We will show that foveation as simulated by controlled, active zooming in conjunction with scale-space techniques allows robust detection and classification of junctions.

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