Articulated motion modeling for activity analysis

Jiang Gao, Robert T. Collins, Alexander G. Hauptmann, Howard D. Wactlar

Research output: Contribution to journalConference articlepeer-review

14 Scopus citations


We propose an algorithm for articulated human motion segmentation that estimates parametric motions of body parts and segments images into moving regions accordingly. Our approach combines robust optical flow estimation, RANSAC, and region segmentation using color and Gaussian shape priors. This combination results in an algorithm that can robustly estimate and segment multiple motions, even for moving regions with small support and in low-resolution images. Based on the raw motion segmentation, consistent body motions are detected over time to characterize human activity. The effectiveness of this approach is demonstrated in a real scenario: characterizing dining activities of patients at a nursing home.

Original languageEnglish (US)
Article number1384809
JournalIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
Issue numberJanuary
StatePublished - 2004
Event2004 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2004 - Washington, United States
Duration: Jun 27 2004Jul 2 2004

All Science Journal Classification (ASJC) codes

  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering


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