Role of Spatiotemporal Oriented Energy Features for Robust Visual Tracking in Video Surveillance

Abstract

We propose an effective approach to take advantage of the rich description provided by Spatiotemporal Oriented Energy features for the purpose of robust tracking. There are two core components in our system. The first one is a compound measure of 'Coherent Motion' and 'Identity Motion Signature' which is introduced based on motion dynamics of the targets. This measure is used for robust optimisation in occluded situations as well as an adaptive template updating scheme. The second component is a state machine which detects various states of the targets based on statistical analysis of their 'Motion Signature'. Empirical evaluations demonstrate improvement in performance of the tracking system along with the role of each component.