Abstract
This paper presents a novel view independent approach on silhouette based human motion analysis for gait recognition applications. Spatio-temporal 1-D signals based on the differences between the outer of binarized silhouette of a motion object and a bounding box placed around silhouette are chosen as the basic image features called the distance vectors. The distance vectors are extracted using four view directions to silhouette. Gait cycle estimation and motion analysis are then performed by using normalized correlation on the distance vectors. Initial experiments for human identification are finally presented. Experimental results on the different test image sequences demonstrate that the proposed algorithm has an encouraging performance with relatively robust, low computational cost, and recognition rate for gait-based human identification.
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Ekinci, M., Gedikli, E. (2005). A Novel Approach on Silhouette Based Human Motion Analysis for Gait Recognition. In: Bebis, G., Boyle, R., Koracin, D., Parvin, B. (eds) Advances in Visual Computing. ISVC 2005. Lecture Notes in Computer Science, vol 3804. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11595755_27
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DOI: https://doi.org/10.1007/11595755_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30750-1
Online ISBN: 978-3-540-32284-9
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