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Estimation of vector fields in unconstrained and inequality constrained variational problems for segmentation and registration

Ünal, Gözde and Slabaugh, Greg (2008) Estimation of vector fields in unconstrained and inequality constrained variational problems for segmentation and registration. Journal of Mathematical Imaging and Vision, 31 (1). pp. 57-72. ISSN 0924-9907 (Print) 1573-7683 (Online)

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Official URL: http://dx.doi.org/10.1007/s10851-008-0064-7

Abstract

Vector fields arise in many problems of computer vision, particularly in non-rigid registration. In this paper, we develop coupled partial differential equations (PDEs) to estimate vector fields that define the deformation between objects, and the contour or surface that defines the segmentation of the objects as well.We also explore the utility of inequality constraints applied to variational problems in vision such as estimation of deformation fields in non-rigid registration and tracking. To solve inequality constrained vector field estimation problems, we apply tools from the Kuhn-Tucker theorem in optimization theory. Our technique differs from recently popular joint segmentation and registration algorithms, particularly in its coupled set of PDEs derived from the same set of energy terms for registration and segmentation. We present both the theory and results that demonstrate our approach.

Item Type:Article
Uncontrolled Keywords:Variational problems - Equality constraints - Inequality constraints - Kuhn-Tucker theorem - Vector fields - Nonrigid registration - Joint registration and segmentation - Tracking
Subjects:Q Science > QA Mathematics > QA075 Electronic computers. Computer science
ID Code:8612
Deposited By:Gözde Ünal
Deposited On:16 Jun 2008 14:20
Last Modified:25 May 2011 14:11

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