Abstract
This paper introduces a novel method of single camera gait reconstruction which is independent of the walking direction and of the camera parameters. Recognizing people by gait has unique advantages with respect to other biometric techniques: the identification of the walking subject is completely unobtrusive and the identification can be achieved at distance. Recently much research has been conducted into the recognition of fronto-parallel gait. The proposed method relies on the very nature of walking to achieve the independence from walking direction. Three major assumptions have been done: human gait is cyclic; the distances between the bone joints are invariant during the execution of the movement; and the articulated leg motion is approximately planar, since almost all of the perceived motion is contained within a single limb swing plane. The method has been tested on several subjects walking freely along six different directions in a small enclosed area. The results show that recognition can be achieved without calibration and without dependence on view direction. The obtained results are particularly encouraging for future system development and for its application in real surveillance scenarios.
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Goffredo, M., Spencer, N., Pearce, D., Carter, J.N., Nixon, M.S. (2007). Human Perambulation as a Self Calibrating Biometric. In: Zhou, S.K., Zhao, W., Tang, X., Gong, S. (eds) Analysis and Modeling of Faces and Gestures. AMFG 2007. Lecture Notes in Computer Science, vol 4778. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75690-3_11
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DOI: https://doi.org/10.1007/978-3-540-75690-3_11
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