Tracking people with twists and exponential maps
Bregler, C.
Malik, J.
Comput. Sci. Div., California Univ., Berkeley, CA ;
This paper appears in: Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on
Publication Date: 23-25 Jun 1998
On page(s): 8-15
Meeting Date: 06/23/1998 - 06/25/1998
Location: Santa Barbara, CA, USA
ISSN: 1063-6919
ISBN: 0-8186-8497-6
References Cited: 27
INSPEC Accession Number: 5985818
Digital Object Identifier: 10.1109/CVPR.1998.698581
Current Version Published: 2002-08-06
Abstract
This paper demonstrates a new visual motion estimation technique
that is able to recover high degree-of-freedom articulated human body
configurations in complex video sequences. We introduce the use of a
novel mathematical technique, the product of exponential maps and twist
motions, and its integration into a differential motion estimation. This
results in solving simple linear systems, and enables us to recover
robustly the kinematic degrees-of-freedom in noise and complex self
occluded configurations. We demonstrate this on several image sequences
of people doing articulated full body movements, and visualize the
results in re-animating an artificial 3D human model. We are also able
to recover and re-animate the famous movements of Eadweard Muybridge's
motion studies from the last century. To the best of our knowledge, this
is the first computer vision based system that is able to process such
challenging footage and recover complex motions with such high accuracy
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