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Visual Surveillance for Movement Rehabilitation

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Języki publikacji
EN
Abstrakty
EN
The paper presents an attempt to create a system for visual surveillance for movement rehabilitation. The Delaunay triangulation was used as a key method for skeletonization of detected human silhouette. Also, the Hough transform was performed on skeletons of selected body parts in order to obtain slants of those body parts. Analysis of slant changes gives information of movement range, number of exercise repetitions and in general, to assessing correctness of performed exercises. The presented results show that - under some circumstances - it is possible to create visual system for such task.
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  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Automatics, Laboratory of Biocybernetics
  • AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of Automatics, Laboratory of Biocybernetics
Bibliografia
  • [1] C.-H. Chuang, et al., Human Action Recognition Using Star Templates and Delaunay Triangulation, International Conference on Intelligent Information Hiding and Multimedia Signal Processing, pp. 179-182, 2008
  • [2] D. Douglas, T. Peucker, Algorithms for the Reduction of the Number of Points Required to Represent a Digitized Line or its Caricature, Cartographica: The International Journal for Geographic Information and Geovisualization, Vol. 10, No.2, pp. 112-122, 1973
  • [3] J.-W. Hsieh, et al., Segmentation of Human Body Parts Using Deformable Triangulation, IEEE Trans. On Systems, Man, and Cybernetics, Vol. 40, No. 3, 2010, pp. 596-610
  • [4] P. Morrison, J.J. Zou, Triangle refinement in a constrained Delaunay triangulation skeleton, Pattern Recognition, Vol. 40, pp. 2754-2765, 2007
  • [5] J.J. Zou, H.H. Chang, H. Yan, Shape skeletonisation by identifying discrete local symmetries, Pattern Recognition, Vol. 34, pp. 1895-1905, 2001
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-55a17900-e78e-418c-8846-2b04133749c4
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