Nonrigid motion analysis based on dynamic refinement of finiteelement models
Tsap, L.V.
Goldof, D.B.
Sarkar, S.
Center for Appl. Sci. Comput., Lawrence Livermore Nat. Lab., CA;
This paper appears in: Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publication Date: May 2000
Volume: 22,
Issue: 5
On page(s): 526-543
ISSN: 0162-8828
References Cited: 38
CODEN: ITPIDJ
INSPEC Accession Number: 6674557
Digital Object Identifier: 10.1109/34.857007
Current Version Published: 2002-08-06
Abstract
We propose new algorithms for accurate nonrigid motion tracking.
Given an initial model representing general knowledge of the object, a
set of sparse correspondences, and incomplete or missing information
about geometry or material properties, we can recover dense motion
vectors using finite element models. The method is based on the
iterative analysis of the differences between the actual and predicted
behaviors. Unknown parameters are recovered using an iterative descent
search for the best nonlinear finite element model that approximates
nonrigid motion of the given object. During this search process, we not
only estimate material properties, but also infer dense point
correspondences from our initial set of sparse correspondences. Thus,
during tracking, the model is refined which, in turn, improves tracking
quality. Experimental results demonstrate the success of the proposed
algorithm. Our work demonstrates the possibility of accurate
quantitative analysis of nonrigid motion in range image sequences with
objects consisting of multiple materials and 3D volumes
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