EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation

EigenTracking: Robust Matching and Tracking of Articulated Objects Using a View-Based Representation (1998)

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by Michael J. Black , Allan D. Jepson

Venue:	International Journal of Computer Vision
Citations:	446 - 15 self

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Datum	Value	Source
TITLE	Eigentracking: Robust matching and tracking of articulated objects using a view-based representation	INFERENCE
AUTHOR NAME	Michael J. Black	SVM HeaderParse 0.1
AUTHOR AFFIL	; Xerox Palo Alto Research Center; ALLAN D. JEPSON ∗ Department of Computer Science, University of Toronto	SVM HeaderParse 0.2
AUTHOR ADDR	; 3333 Coyote Hill Road, Palo Alto, CA 94304; Toronto, Ontario M5S 3H5 Canada	SVM HeaderParse 0.1
ABSTRACT	Abstract. This paper describes an approach for tracking rigid and articulated objects using a view-based representation. The approach builds on and extends work on eigenspace representations, robust estimation techniques, and parameterized optical flow estimation. First, we note that the least-squares image reconstruction of standard eigenspace techniques has a number of problems and we reformulate the reconstruction problem as one of robust estimation. Second we define a “subspace constancy assumption ” that allows us to exploit techniques for parameterized optical flow estimation to solve for both the view of an object and the affine transformation between the eigenspace and the image. To account for large affine transformations between the eigenspace and the image we define a multi-scale eigenspace representation and a coarse-to-fine matching strategy. Finally, we use these techniques to track objects over long image sequences in which the objects simultaneously undergo both affine image motions and changes of view. In particular we use this “EigenTracking ” technique to track and recognize the gestures of a moving hand.	SVM HeaderParse 0.1
YEAR	1996	INFERENCE
VENUE	International Journal of Computer Vision	INFERENCE
VENUE TYPE	CONFERENCE	INFERENCE
PAGES	329--342	INFERENCE
VOLUME	26	INFERENCE
CITATIONS	33 found	ParsCit 1.0