2D human pose estimation in TV shows

<p>The goal of this work is fully automatic 2D human pose estimation in unconstrained TV shows and feature films. Direct pose estimation on this uncontrolled material is often too difficult, especially when knowing nothing about the location, scale, pose, and appearance of the person, or even...

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Main Authors: Ferrari, V, Marín-Jiménez, M, Zisserman, A
Format: Conference item
Language:English
Published: Springer 2009
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author Ferrari, V
Marín-Jiménez, M
Zisserman, A
author_facet Ferrari, V
Marín-Jiménez, M
Zisserman, A
author_sort Ferrari, V
collection OXFORD
description <p>The goal of this work is fully automatic 2D human pose estimation in unconstrained TV shows and feature films. Direct pose estimation on this uncontrolled material is often too difficult, especially when knowing nothing about the location, scale, pose, and appearance of the person, or even whether there is a person in the frame or not.</p> <p>We propose an approach that progressively reduces the search space for body parts, to greatly facilitate the task for the pose estimator. Moreover, when video is available, we propose methods for exploiting the temporal continuity of both appearance and pose for improving the estimation based on individual frames.</p> <p>The method is fully automatic and self-initializing, and explains the spatio-temporal volume covered by a person moving in a shot by soft-labeling every pixel as belonging to a particular body part or to the background. We demonstrate upper-body pose estimation by running our system on four episodes of the TV series&nbsp;<em>Buffy the vampire slayer</em>&nbsp;(i.e. three hours of video). Our approach is evaluated quantitatively on several hundred video frames, based on ground-truth annotation of 2D poses. Finally, we present an application to full-body action recognition on the Weizmann dataset.</p>
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spelling oxford-uuid:7ee5fdee-19d6-48b7-a050-e3fed083013f2025-01-22T13:33:06Z2D human pose estimation in TV showsConference itemhttp://purl.org/coar/resource_type/c_5794uuid:7ee5fdee-19d6-48b7-a050-e3fed083013fEnglishSymplectic ElementsSpringer2009Ferrari, VMarín-Jiménez, MZisserman, A<p>The goal of this work is fully automatic 2D human pose estimation in unconstrained TV shows and feature films. Direct pose estimation on this uncontrolled material is often too difficult, especially when knowing nothing about the location, scale, pose, and appearance of the person, or even whether there is a person in the frame or not.</p> <p>We propose an approach that progressively reduces the search space for body parts, to greatly facilitate the task for the pose estimator. Moreover, when video is available, we propose methods for exploiting the temporal continuity of both appearance and pose for improving the estimation based on individual frames.</p> <p>The method is fully automatic and self-initializing, and explains the spatio-temporal volume covered by a person moving in a shot by soft-labeling every pixel as belonging to a particular body part or to the background. We demonstrate upper-body pose estimation by running our system on four episodes of the TV series&nbsp;<em>Buffy the vampire slayer</em>&nbsp;(i.e. three hours of video). Our approach is evaluated quantitatively on several hundred video frames, based on ground-truth annotation of 2D poses. Finally, we present an application to full-body action recognition on the Weizmann dataset.</p>
spellingShingle Ferrari, V
Marín-Jiménez, M
Zisserman, A
2D human pose estimation in TV shows
title 2D human pose estimation in TV shows
title_full 2D human pose estimation in TV shows
title_fullStr 2D human pose estimation in TV shows
title_full_unstemmed 2D human pose estimation in TV shows
title_short 2D human pose estimation in TV shows
title_sort 2d human pose estimation in tv shows
work_keys_str_mv AT ferrariv 2dhumanposeestimationintvshows
AT marinjimenezm 2dhumanposeestimationintvshows
AT zissermana 2dhumanposeestimationintvshows