Nonrigid motion analysis based on dynamic refinement of finiteelement models
Tsap, L.V.
Goldgof, D.B.
Sarkar, S.
Dept. of Comput. Sci. & Eng., Univ. of South Florida, Tampa, FL;
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): 728-734
Meeting Date: 06/23/1998 - 06/25/1998
Location: Santa Barbara, CA, USA
ISSN: 1063-6919
ISBN: 0-8186-8497-6
References Cited: 14
INSPEC Accession Number: 5985920
Digital Object Identifier: 10.1109/CVPR.1998.698684
Current Version Published: 2002-08-06
Abstract
In this paper we propose new algorithms for accurate nonrigid
motion tracking. Given only a set of sparse correspondences and
incomplete or missing information about geometry or material properties,
we recover dense motion vectors using nonlinear finite element models.
The method is based on the iterative analysis of the differences between
the actual and predicted behavior. Large differences indicate that an
object's properties are not captured properly by the model. Feedback
from the images during the motion allows the refinement of the model by
minimizing the error between the expected and true position of the
object's points. Unknown parameters are recovered using an iterative
descent search for the best model that approximates nonrigid motion of
the given object. Thus, during tracking the model is refined which, in
turn, improves tracking quality. The method was applied successfully to
man-made elastic materials and human skin to recover unknown elasticity,
to complex 3-D objects to find details of their geometry, and to a hand
motion analysis application
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