GA-STIP: Action Recognition in Multi-Channel Videos With Geometric Algebra Based Spatio-Temporal Interest Points

Abstract

Spatiotemporal interest points (STIPs) are often extracted for action recognition in videos. But most of the current interest point detection methods are not suitable for multi-channel videos. In this paper, a new geometric algebra (GA)-based STIP detection method is proposed for action recognition in multi-channel videos. Specifically, we take the advantage of GA to represent multi-channel videos and develop a new method to obtain multi-scale space, and then GA-based difference of Gaussian is computed to detect STIPs. Experimental results show that GA-STIP method can achieve better performance for multi-channel video action recognition.