This paper1 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. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Ekinci, M., & Gedikli, E. (2005). A novel approach on silhouette based human motion analysis for gait recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3804 LNCS, pp. 219–226). https://doi.org/10.1007/11595755_27
Mendeley helps you to discover research relevant for your work.