We describe a new method for automatic gait recognition based on analysing the symmetry of human motion, by using the Generalised Symmetry Operator. This operator, rather than relying on the borders of a shape or on general appearance, locates features by their symmetrical properties. This approach is reinforced by the psychologists' view that gait is a symmetrical pattern of motion and by other works. We applied our new method to two different databases and derived gait signatures for silhouettes and optical flow. The results show that the symmetry properties of individuals' gait appear to be unique and can indeed be used for recognition. We have so far achieved promising recognition rates of over 95%. Performance analysis also suggests that symmetry enjoys practical advantages such as relative immunity to noise and missing frames, and with capability to handle occlusion. © Springer-Verlag 2001.
CITATION STYLE
Hayfron-Acquah, J. B., Nixon, M. S., & Carter, J. N. (2001). Automatic gait recognition by symmetry analysis. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2091 LNCS, 272–277. https://doi.org/10.1007/3-540-45344-x_40
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