Self-occlusion robust 3D human pose tracking from monocular image sequence

Nam Gyu Cho, Alan Yuille, Seong Whan Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Pose tracking technique has great potential for many applications such as marker-free human motion capture system, Human Computer Interactions (HCI), and video surveillance. Though many methods are introduced during last decades, self-occlusion - one body part is occluded by another one - is still considered one of the most difficult problems for 3D human pose tracking. In this paper, we propose a self-occlusion state estimation method. A MRF (Markov Random Field) is used to model the occlusion state which represents the pairwise depth order between two human body parts. A novel estimation method is proposed to infer a body pose and an occlusion state separately. HumanEva dataset is used for testing the proposed method. In order to evaluate and quantify how often the occlusion state changes, we label the ground truth of occlusion state.

Original languageEnglish
Title of host publicationProceedings 2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
Pages254-257
Number of pages4
DOIs
Publication statusPublished - 2012
Event2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012 - Seoul, Korea, Republic of
Duration: 2012 Oct 142012 Oct 17

Publication series

NameConference Proceedings - IEEE International Conference on Systems, Man and Cybernetics
ISSN (Print)1062-922X

Other

Other2012 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2012
Country/TerritoryKorea, Republic of
CitySeoul
Period12/10/1412/10/17

Keywords

  • 3D human pose tracking
  • Motion analysis
  • Self-occlusion

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Human-Computer Interaction

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