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14 March 2005 Modeling of pedestrian motion for recognition
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Proceedings Volume 5685, Image and Video Communications and Processing 2005; (2005)
Event: Electronic Imaging 2005, 2005, San Jose, California, United States
Good pedestrian classifiers that analyze static images for presence of pedestrians are in existence. However, even a low false positive error rating is sufficient to flood a real system with false warnings. We address the problem of pedestrian motion (gait) modeling and recognition using sequences of images rather than static individual frames, thereby exploiting information in the dynamics. We use two different representations and corresponding distances for gait sequences. In the first a gait is represented as a manifold in a lower dimensional space corresponding to gait images. In the second a gait image sequence is represented as the output of a dynamical system whose underlying driving process is an action like walking or running. We examine distance functions corresponding to these representations. For dynamical systems we formulate distances derived based on parameters of the system taking into account both the structure of the output space and the dynamics within it. Given appearance based models we present results demonstrating the discriminative power of the proposed distances
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Payam Saisan, Swarup Medasani, Narayan Srinivasa, and Yuri Owechko "Modeling of pedestrian motion for recognition", Proc. SPIE 5685, Image and Video Communications and Processing 2005, (14 March 2005);


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