In this chapter we apply the Local Binary Pattern on Three Orthogonal Planes (LBP-TOP) descriptor to the field of human action recognition. We modified this spatio-temporal descriptor using LBP and CS-LBP techniques combined with gradient and Gabor images. Moreover, we enhanced its performances by performing the analysis on more slices located at different time intervals or at different views. A video sequence is described as a collection of spatial-temporal words after the detection of space-time interest points and the description of the area around them. Our contribution has been in the description part, showing LBP-TOP to be 1) a promising descriptor for human action classification purposes and 2) we have developed several modifications and extensions to the descriptor in order to enhance its performance in human motion recognition, showing the method to be computationally efficient.
|Title of host publication
|Intelligent Video Event Analysis and Understanding
|Jianguo Zhang, Ling Shao, Lei Zhang, Graeme A. Jones
|Place of Publication
|Number of pages
|Published - 2011
|Studies in Computational Intelligence