The Robotics Institute

Carnegie Mellon Robotics Institute

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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.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Text Reference

David Fouhey, Vincent Delaitre, Abhinav Gupta, Alexei A. Efros, Ivan Laptev, and Josef Sivic, "People Watching: Human Actions as a Cue for Single View Geometry," European Conference on Computer Vision (ECCV), October, 2012.

BibTeX Reference

@inproceedings{Fouhey_2012_7248,
   author = "David Fouhey and Vincent Delaitre and Abhinav Gupta and Alexei A. Efros and Ivan Laptev and Josef Sivic",
   title = "People Watching: Human Actions as a Cue for Single View Geometry",
   booktitle = "European Conference on Computer Vision (ECCV)",
   month = "October",
   year = "2012",
}

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