People Watching: Human Actions as a Cue for Single View Geometry
chairman: Aude Oliva, Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology, MIT
chairman: Silvio Savarese, Department of Electrical Engineering and Computer Science, University of Michigan
published: Nov. 12, 2012, recorded: October 2012, views: 277
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We present an approach which exploits the coupling between human actions and scene geometry. We investigate the use of human pose as a cue for single-view 3D scene understanding. Our method builds upon recent advances in still-image pose estimation to extract functional and geometric constraints about the scene. These constraints are then used to improve state-of-the-art single-view 3D scene understanding approaches. The proposed method is validated on a collection of monocular time-lapse sequences collected from YouTube and a data set of still images of indoor scenes. We demonstrate that observing people performing different actions can significantly improve estimates of 3D scene geometry.
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