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Abstract: This paper describes a method for the robust tracking of rigid head motion from video. This method uses a 3D ellipsoidal model of the head and interprets the optical flow in terms of the possible rigid motions of the model. This method is robust to large angular and translational motions of the head and is not subject to the singularities of a 2D model. The method has been successfully applied to heads with a variety of shapes, hair styles, etc. This method also has the advantage of accurately... (Update)
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BibTeX entry: (Update)
S. Basu, I. Essa, and A. Pentland. Motion regularization for model-based head tracking. In Intl. Conf. on Pattern Recognition (ICPR '96), Vienna, Austria, 1996. http://citeseer.ist.psu.edu/basu96motion.html More
@misc{ basu96motion,
author = "S. Basu and I. Essa and A. Pentland",
title = "Motion regularization for model-based head tracking",
text = "S. Basu, I. Essa, and A. Pentland. Motion regularization for model-based
head tracking. In Intl. Conf. on Pattern Recognition (ICPR '96), Vienna,
Austria, 1996.",
year = "1996",
url = "citeseer.ist.psu.edu/basu96motion.html" }
Citations (may not include all citations):349 Hierarchical model-based motion estimation (context) - Bergen, Anandan et al. - 1992 ACM DBLP
160 Determining three-dimensional motion and structure from opti.. (context) - Adiv - 1985
58 Face recognition from one example view - Beymer, Poggio ACM DBLP
55 Recursive estimation of motion (context) - Azarbayejani, Pentland - 1995
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