Bio-inspired model with dual visual pathways for human action recognition

Spatio-temporal interesting points feature is a key technology for a wide class of computer vision approaches to recognize human actions. In this paper, a novel bio-inspired model based spatio-temporal interesting points (BIM-STIP) framework is proposed. Different from traditional STIP framework, the introduction of bio-inspired model provides a biological theory for interest points detection and spatio-temporal descriptor construction. Moreover, unlike existing bio-inspired model for action recognition with a single pathway, a dual pathway joint model with dorsal stream and ventral stream is constructed. Finally, this paper demonstrate how these feature to be used in a standard STIP framework for action recognition. Promising experimental results show that the proposed framework outperforms most of existing algorithms in action recognition, which encourages us to develop the BIM-STIP framework to other applications in future.