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People Watching: Human Actions as a Cue for Single View Geometry

David Fouhey 1 Vincent Delaitre 2 Abhinav Gupta 1 Alexei A. Efros 1 Ivan Laptev 3 Josef Sivic 3
3 WILLOW - Models of visual object recognition and scene understanding
CNRS - Centre National de la Recherche Scientifique : UMR8548, Inria Paris-Rocquencourt, DI-ENS - Département d'informatique de l'École normale supérieure
Abstract : 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 dataset 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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https://hal.inria.fr/hal-01060874
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David Fouhey, Vincent Delaitre, Abhinav Gupta, Alexei A. Efros, Ivan Laptev, et al.. People Watching: Human Actions as a Cue for Single View Geometry. ECCV'12 - 12th European Conference on Computer Vision, Oct 2012, Florence, Italy. pp.732-735, ⟨10.1007/978-3-642-33715-4_53⟩. ⟨hal-01060874⟩

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