Show simple item record Liu, Yonghuai 2011-11-02T12:06:46Z 2011-11-02T12:06:46Z 2010-01-01
dc.identifier.citation Liu , Y 2010 , ' Automatic Range Image Registration in the Markov Chain ' IEEE Transactions on Pattern Analysis and Machine Intelligence , vol 32 , no. 1 , pp. 12-29 . DOI: 10.1109/TPAMI.2008.280 en
dc.identifier.issn 0162-8828
dc.identifier.other PURE: 173233
dc.identifier.other PURE UUID: ffa6999b-884d-4e9b-a12b-5bbfef1e8683
dc.identifier.other dspace: 2160/7673
dc.identifier.other RAD_Outputs_All_ID_Import_20121105.csv: row: 357
dc.identifier.other Scopus: 77956026620
dc.identifier.other PubMed: 19926896
dc.description Liu, Y. (2010). Automatic Range Image Registration in the Markov Chain. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32 (1), 12-29 en
dc.description.abstract In this paper, a novel entropy that can describe both long and short-tailed probability distributions of constituents of a thermodynamic system out of its thermodynamic limit is first derived from the Lyapunov function for a Markov chain. We then maximize this entropy for the estimation of the probabilities of possible correspondences established using the traditional closest point criterion between two overlapping range images. When we change our viewpoint to look carefully at the minimum solution to the probability estimate of the correspondences, the iterative range image registration process can also be modeled as a Markov chain in which lessons from past experience in estimating those probabilities are learned. To impose the two-way constraint, outliers are explicitly modeled due to the almost ubiquitous occurrence of occlusion, appearance, and disappearance of points in either image. The estimated probabilities of the correspondences are finally embedded into the powerful mean field annealing scheme for global optimization, leading the camera motion parameters to be estimated in the weighted least-squares sense. A comparative study using real images shows that the proposed algorithm usually outperforms the state-of-the-art ICP variants and the latest genetic algorithm for automatic overlapping range image registration. en
dc.format.extent 18 en
dc.language.iso eng
dc.relation.ispartof IEEE Transactions on Pattern Analysis and Machine Intelligence en
dc.rights en
dc.title Automatic Range Image Registration in the Markov Chain en
dc.type /dk/atira/pure/researchoutput/researchoutputtypes/contributiontojournal/article en
dc.contributor.institution Department of Computer Science en
dc.contributor.institution Vision, Graphics and Visualisation Group en
dc.description.status Peer reviewed en

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