Title :
Bio-inspired model with dual visual pathways for human action recognition
Author :
Bolun Cai ; Xiangmin Xu ; Chunmei Qing
Author_Institution :
Sch. of Electron. & Inf. Eng., South China Univ. of Technol., Guangzhou, China
Abstract :
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.
Keywords :
feature extraction; image motion analysis; image recognition; video signal processing; BIM-STIP framework; bio-inspired model based spatio-temporal interesting points; biological theory; dorsal stream; dual pathway joint model; dual visual pathways; human action recognition; interest points detection; spatio-temporal descriptor construction; ventral stream; video HAR; Biological system modeling; Brain modeling; Computational modeling; Databases; Detectors; Feature extraction; Visualization; Bio-Inspired Model; dual visual pathways; human action recognition;
Conference_Titel :
Communication Systems, Networks & Digital Signal Processing (CSNDSP), 2014 9th International Symposium on
Conference_Location :
Manchester
DOI :
10.1109/CSNDSP.2014.6923838