Action Recognition Using Visual-Neuron Feature

Ning LI  De XU  

IEICE TRANSACTIONS on Information and Systems   Vol.E92-D   No.2   pp.361-364
Publication Date: 2009/02/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E92.D.361
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Recognition, Computer Vision
neurobiological approach for action recognition (NAAR),  visual-neuron template (VNT),  visual-neuron feature (VNF),  visual cortex,  

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This letter proposes a neurobiological approach for action recognition. In this approach, actions are represented by a visual-neuron feature (VNF) based on a quantitative model of object representation in the primate visual cortex. A supervised classification technique is then used to classify the actions. The proposed VNF is invariant to affine translation and scaling of moving objects while maintaining action specificity. Moreover, it is robust to the deformation of actors. Experiments on publicly available action datasets demonstrate the proposed approach outperforms conventional action recognition models based on computer-vision features.