Abstract
Human gait is an attractive modality for recognizing people at a distance. In this paper we adopt an appearance-based approach to the problem of gait recognition. The width of the outer contour of the binarized silhouette of a walking person is chosen as the basic image feature. Different gait features are extracted from the width vector such as the dowsampled, smoothed width vectors, the velocity profile etc. and sequences of such temporally ordered feature vectors are used for representing a person’s gait. We use the dynamic time-warping (DTW) approach for matching so that non-linear time normalization may be used to deal with the naturally-occuring changes in walking speed. The performance of the proposed method is tested using different gait databases.
Partially supported by the DARPA/ONR grant N00014-00-1-0908.
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References
J. Cutting and L. Kozlowski, “Recognizing friends by their walk:gait perception without familiarity cues,” Bulletin of the Psychonomic Society, vol. 9, pp. 353–356, 1977.
D. Cunado, J.M. Nash, M. S. Nixon, and J.N. Carter, “Gait extraction and description by evidence-gathering,” Proc. of the International Conference on Audio and Video Based Biometric Person Authentication, pp. 43–48, 1995.
L. Lee and W.E. L. Grimson, “Gait analysis for recognition and classification,” Proceedings of the IEEE Conference on Face and Gesture Recognition, pp. 155–161, 2002.
A. Kale, N. Cuntoor, and R. Chellappa, “A framework for activity-specific human recognition,” Proceedings of the International Conference on Acoustics, Speech and Signal Processing (Orlando, FL), May 2002.
P. S. Huang, C. J. Harris, and M. S. Nixon, “Recognizing humans by gait via parametric canonical space,” Artificial Intelligence in Engineering, vol. 13, no. 4, pp. 359–366, October 1999.
A.F. Bobick and A. Johnson, “Gait extraction and description by evidencegathering,” Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2001.
Jinu Mariam Zacharia, “Text-independent speaker verification using segmental, suprasegmental and source features,” M. S. thesis, IIT Madras Chennai India, March 2002.
L. Rabiner and H. Juang, Fundam entals of speech recognition, Prentice Hall, 1993.
W. I Scholhorn, Nigg B.M, D. J. Stephanshyn, and W. Liu, “Identification of individual walking patterns using time discrete and time continuous data sets,” Gait and Posture, vol. 15, pp. 180–186, 2002.
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Kale, A., Cuntoor, N., Yegnanarayana, B., Rajagopalan, A., Chellappa, R. (2003). Gait Analysis for Human Identification. In: Kittler, J., Nixon, M.S. (eds) Audio- and Video-Based Biometric Person Authentication. AVBPA 2003. Lecture Notes in Computer Science, vol 2688. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44887-X_82
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DOI: https://doi.org/10.1007/3-540-44887-X_82
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