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Title:Decomposition of Range Images Using Markov Random Fields
Authors: Andreas Pilcher ; Robert Fisher ; Markus Vincze
Date: 2004
Publication Title:Proc. Int. Conf. on Image Proc. (ICIP)
Publication Type:Conference Paper
Page Nos:1205-1208
Abstract:
This paper describes a computational model for deriving a decomposition of objects from laser rangefinder data. The process aims to produce a set of parts defined by compactness and smoothness of surface connectivity. Relying on a general decomposition rule, any kind of objects made up of free-form surfaces are partitioned. A robust method to partition the object based on Markov Random Fields (MRF), which allows to incorporate prior knowledge, is presented. Shape index and curvedness descriptors along with discontinuity and concavity distributions are introduced to classify labels correctly. In addition, a novel way to classify the shape of a surface is proposed resulting in a better distinction of concave, convex and saddle shapes. To achieve a reliable classification a multi-scale method provides a stable estimation of the shape index.
Copyright:
Copyright 2004 IEEE. Reprinted from Proc. Int. Conf. on Image Proc. (ICIP), Singapore, pp 1205-1208.
This material is posted here with permission of the IEEE.Such permission of the IEEE does not in any way imply IEEE endorsement of any of Edinburgh's products or services. Internal or personal use of thismaterial is permitted. However, permission to reprint/republish this materialfor advertising or promotional purposes or for creating new collective worksfor resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.
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Bibtex format
@InProceedings{EDI-INF-RR-0781,
author = { Andreas Pilcher and Robert Fisher and Markus Vincze },
title = {Decomposition of Range Images Using Markov Random Fields},
book title = {Proc. Int. Conf. on Image Proc. (ICIP)},
year = 2004,
pages = {1205-1208},
}


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