Fuzzy contour tracking of human silhouettes

Authors:
Timothy C. Havens;Gregory L. Alexander;James M. Keller;Marjorie Skubic;Marilyn Rantz
Affiliations:
Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO;Sinclair School of Nursing, University of Missouri, Columbia, MO;Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO;Department of Electrical and Computer Engineering, University of Missouri, Columbia, MO;Sinclair School of Nursing, University of Missouri, Columbia, MO
Venue:
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Year:
2009

Citing 3
Cited 0

Understanding human behavior from motion imagery

Machine Vision and Applications - Special issue: Human modeling, analysis, and synthesis
Motion capture and visualization of the hip joint with dynamic MRI and optical systems: Research Articles

Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Motion detection using an improved colour model

ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part II

Quantified Score

Hi-index	0.00

Visualization

Abstract

Video-based tracking of contours on the human body has been shown to be useful for many applications, including gait and gesture recognition, posture estimation, and activity analysis. We present a contour tracking method that incorporates a novel edge feature and fuzzy contour template. We apply our method in tracking the motions of older adults exercising in a gym environment. The output of our system is a dynamic fuzzy representation of the spine angle of the subject. We show that the method described in this paper is capable of tracking contours even in cases where human silhouette extraction is poor.