Compositional Structure Learning for Action Understanding

21 Oct 2014 Ran Xu Gang Chen Caiming Xiong Wei Chen Jason J. Corso

The focus of the action understanding literature has predominately been classification, how- ever, there are many applications demanding richer action understanding such as mobile robotics and video search, with solutions to classification, localization and detection. In this paper, we propose a compositional model that leverages a new mid-level representation called compositional trajectories and a locally articulated spatiotemporal deformable parts model (LALSDPM) for fully action understanding... (read more)

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