@inproceedings{1718f52c81154f2ea5d6b7e98e5cf299,
title = "People watching: Human actions as a cue for single view geometry",
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.",
author = "Fouhey, {David F.} and Vincent Delaitre and Abhinav Gupta and Efros, {Alexei A.} and Ivan Laptev and Josef Sivic",
year = "2012",
doi = "10.1007/978-3-642-33715-4_53",
language = "English (US)",
isbn = "9783642337147",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 5",
pages = "732--745",
booktitle = "Computer Vision, ECCV 2012 - 12th European Conference on Computer Vision, Proceedings",
edition = "PART 5",
note = "12th European Conference on Computer Vision, ECCV 2012 ; Conference date: 07-10-2012 Through 13-10-2012",
}