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Incorporating illumination constraints in deformable models

  • University of Pennsylvania

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

27 Scopus citations

Abstract

We present a method for the integration of illumination constraints within a deformable model framework. These constraints are incorporated as nonlinear holonomic constraints in the Lagrange equations of motion governing the deformation of the model. For improved numerical performance we employ the Baumgarte stabilization method. Our methodology is general and can be used for a broad range of illumination constraints. This approach avoids commonly used approximations in shape from shading, such as linearization, and the use of partial differential equations, which require initial boundary conditions. Furthermore, global and local parameterizations of the deformable models allow an improved estimation of shape from shading. We demonstrate this improvement over previously used approaches through a series of experiments on standardized sets of real and synthetic data.

Original languageEnglish
Title of host publicationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Pages322-329
Number of pages8
DOIs
StatePublished - 1998
EventProceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Santa Barbara, CA, USA
Duration: Jun 23 1998Jun 25 1998

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN (Print)1063-6919

Conference

ConferenceProceedings of the 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition
CitySanta Barbara, CA, USA
Period06/23/9806/25/98

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