A Spatiotemporal Saliency Framework

Yang Liu, Christos-Savvas Bouganis, Peter Y. K. Cheung

Abstract: This paper presents a novel bio-inspired spatiotemporal saliency framework. The framework incorporates spatial feature detection, feature tracking and motion prediction in order to generate a spatiotemporal saliency map. Experimental results demonstrate its ability and robustness to produce saliency responses to motion pop-up phenomena that are in line with humans responses. Moreover, the limited storage requirements permit real-time implementations of the proposed framework.