Articulated Motion Modeling for Activity Analysis

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 com...

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Bibliographic Details
Published in2004 Conference on Computer Vision and Pattern Recognition Workshop p. 20
Main Authors Jiang Gao, Collins, R.T., Hauptmann, A.G., Wactlar, H.D.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2004
Subjects
Biological system modeling
Computer vision
Humans
Image motion analysis
Image segmentation
Motion analysis
Motion estimation
Motion segmentation
Nonlinear optics
Robustness
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Summary: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.
DOI:10.1109/CVPR.2004.303