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Stereovision based travel aid system for people with a vision impairment

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Języki publikacji
EN
Abstrakty
EN
Rapidly growing computation power of portable devices together with significant progress in computer vision allow to adopt new nearly realtime solutions for aiding the blind persons during the travel. Recent solutions for people with vision impairment are dedicated to support the user during the decision process, giving the information about divert obstacles located in the environment. Commonly they are using ultrasonic echo-location for obstacles tracking without its classification and recognition. Therefore the solution presented in this paper engages the stereo camera and image processing algorithms to facilitate its user with object detection and recognition mechanisms. The inference engine combined together with ontology based problem modeling allows to handle the risk, predict possible user's moves and provide the user with appropriate set of tips that will eliminate or reduce the discovered risk.
Twórcy
autor
  • Institute of Telecommunications University of Technology & Life Sciences Kaliskiego 7, 85-796 Bydgoszcz, Poland, rafal.kozik@upt.edu.pl
Bibliografia
  • [1] P. Pełczyński. Travel Aid System for the Blind, Image Processing and Communications Challenges, p. 324-333, 2009.
  • [2] The Miniguide project homepage, http://www.gdp-research.com.au.
  • [3] J. Sun, Y. Li, S. Kang, H. Shum. Symmetric stereo matching for occlusion handling, In CVPR, pages II: 399-406, 2005.
  • [4] V. Kolmogorov, R. Zabih. Computing visual correspondence with occlusions via graph cuts. In I, pages II: 508-515, 2001.
  • [5] S. Birchfield, C. Tomasi. Depth Discontinuities by Pixel-to-Pixel Stereo. International Journal of Computer Vision, 35(3): 269-293, December 1999.
  • [6] J. Sivic, A. Zisserman. Efficient Visual Search for Objects in Videos. Proceedings of the IEEE, 2008.
  • [7] D. Kirasic, D. Basch. Ontology-Based Design Pattern Recognition. Lecture Notes in Computer Science, 2009.
  • [8] R. Kozik, SMAS - Stereovision Mobility Aid System for People with a Vision Impairment, In: R. S. Choras (Ed.): Image Processing and Communication Challenges 2, Advances in Soft Computing, 315-322, Springer, 2010.
  • [9] A. R. J. Francois, R. Nevatia, J. Hobbs, R. C. Bolles. VERL: an ontology framework for representing and annotating video events. IEEE MultiMedia, Vol. 12 No. 4, pp.76-86, 2005.
  • [10] F. Latfi, B. Lefebvre, C. Descheneaux. Ontology-based management of the telehealth smart home, dedicated to elderly in loss of cognitive autonomy. CEUR Workshop Proceedings, Vol. 258, 2007.
  • [11] Torralba, R. Fergus, Y. Weiss. Small codes and large databases for recognition. In CVPR, 2008.
  • [12] J. Philbin, O. Chum, M. Isard, J. Sivic, A. Zisserman. Lost in quantization: Improving particular object retrieval in large scale image databases. In: CVPR, 2008.
  • [13] P. F. Felzenszwalb, D. P. Huttenlocher. Efficient belief propagation for early vision. In CVPR, pages 1: 261-268, 2004.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0057-0008
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