Appearance Based Behavior Recognition by Event Driven Selective Attention

Most of behavior recognition methods proposed so far share the limitations of bottom-up analysis, and singleobject assumption; the bottom-up analysis can be confused by erroneous and missing image features and the singleobject assumption prevents us from analyzing image sequences including multiple moving objects. This paper presents a robust behavior recognition method free from these limitations. Our method is best characterized by 1) top-down image feature extraction by selective attention mechanism, 2) object discrimination by colored-token propagation, and 3) integration of multi-viewpoint images. Extensive experiments of human behavior recognition in real world environments demonstrate the soundness and robustness of our method.

• Type: Conference
• Year: 1998
• Where: CVPR
• Authors: Toshikazu Wada, Takashi Matsuyama
• Keywords: Behavior Recognition Method, Bottom-up Analysis, Computer Vision, CVPR 1998, Singleobject Assumption