Vision-based motion capture of interacting multiple people

Hiroaki Egashira, Atsushi Shimada, Daisaku Arita, Rin Ichiro Taniguchi

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

2 Citations (Scopus)


Vision-based motion capture is getting popular for acquiring human motion information in various interactive applications. To enlarge its applicability, we have been developing a vision-based motion capture system which can estimate the postures of multiple people simultaneously using multiview image analysis. Our approach is divided into the following two phases: at first, extraction, or segmentation, of each person in input multiview images; then, posture analysis for one person is applied to the segmented region of each person. The segmentation is realized in the voxel space, which is reconstructed by visual cone intersection of multiview silhouettes. Here, a graph cut algorithm is employed to achieve optimal segmentation. Posture analysis is based on a model-based approach, where a skeleton model of human figure is matched with the multiview silhouettes based on a particle filter and physical constraints on human body movement. Several experimental studies show that the proposed method acquires human postures of multiple people correctly and efficiently even when they touch each otter.

Original languageEnglish
Title of host publicationImage Analysis and Processing - ICIAP 2009 - 15th International Conference, Proceedings
Number of pages10
Publication statusPublished - 2009
Event15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings - Vietri sul Mare, Italy
Duration: Sept 8 2009Sept 11 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5716 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other15th International Conference on Image Analysis and Processing - ICIAP 2009, Proceedings
CityVietri sul Mare

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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