Action Recognition Using Visual-Neuron Feature
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概要
- 論文の詳細を見る
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.
- （社）電子情報通信学会の論文
- 2009-02-01
著者
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XU De
Institute of Computer Science and Engineering, Beijing Jiaotong University
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Xu De
Institute Of Computer Science And Engineering Beijing Jiaotong University
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Xu De
Institute Of Computer & Engineering Beijing Jiaotong University
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Li Ning
Institute Of Computer Science And Engineering Beijing Jiaotong University
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Li Ning
Institute Of Communications Engineering Pla University Of Science And Technology
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