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Lecture Notes in Computer Science
We propose a model to combine per-frame and per-track cues for action recognition. With multiple targets in a scene, our model simultaneously captures the natural harmony of an individual's action in a scene and the flow of actions of an individual in a video sequence, inferring valid tracks in the process. Our motivation is based on the unlikely discordance of an action in a structured scene, both at the track level and the frame level (e.g., a person dancing in a crowd of joggers). While wedoi:10.1007/978-3-642-33718-5_9 fatcat:hji47lhygfbgvdymul2pv4fuui