A Bio-Inspired Modeling of Visual Information Processing for Action Recognition


KIPS Transactions on Software and Data Engineering, Vol. 3, No. 8, pp. 299-308, Aug. 2014
10.3745/KTSDE.2014.3.8.299, Full Text:

Abstract

Various literatures related computing of information processing have been recently shown the researches inspired from the remarkably excellent human capabilities which recognize and categorize very complex visual patterns such as body motions and facial expressions. Applied from human``s outstanding ability of perception, the classification function of visual sequences without context information is specially crucial task for computer vision to understand both the coding and the retrieval of spatio-temporal patterns. This paper presents a biological process based action recognition model of computer vision, which is inspired from visual information processing of human brain for action recognition of visual sequences. Proposed model employs the structure of neural fields of bio-inspired visual perception on detecting motion sequences and discriminating visual patterns in human brain. Experimental results show that proposed recognition model takes not only into account several biological properties of visual information processing, but also is tolerant of time-warping. Furthermore, the model allows robust temporal evolution of classification compared to researches of action recognition. Presented model contributes to implement bio-inspired visual processing system such as intelligent robot agent, etc.


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Cite this article
[IEEE Style]
J. O. Kim, "A Bio-Inspired Modeling of Visual Information Processing for Action Recognition," KIPS Transactions on Software and Data Engineering, vol. 3, no. 8, pp. 299-308, 2014. DOI: 10.3745/KTSDE.2014.3.8.299.

[ACM Style]
Jin Ok Kim. 2014. A Bio-Inspired Modeling of Visual Information Processing for Action Recognition. KIPS Transactions on Software and Data Engineering, 3, 8, (2014), 299-308. DOI: 10.3745/KTSDE.2014.3.8.299.