Penalizing Closest Point Sharing for Automatic Free Form Shape Registration

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dc.contributor.author Liu, Yonghuai
dc.date.accessioned 2011-11-01T16:32:38Z
dc.date.available 2011-11-01T16:32:38Z
dc.date.issued 2011-05-01
dc.identifier.citation Liu , Y 2011 , ' Penalizing Closest Point Sharing for Automatic Free Form Shape Registration ' IEEE Transactions on Pattern Analysis and Machine Intelligence , vol 33 , no. 5 , pp. 1058-1064 . en
dc.identifier.issn 0162-8828
dc.identifier.other PURE: 173218
dc.identifier.other dspace: 2160/7671
dc.identifier.uri http://hdl.handle.net/2160/7671
dc.description Liu, Y. (2011). Penalizing Closest Point Sharing for Automatic Free Form Shape Registration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 33 (5), 1058-1064 en
dc.description.abstract For accurate registration of overlapping free form shapes, different points in one shape must select different points in another as their most sensible correspondents. To reach this ideal state, in this paper we develop a novel algorithm to penalize those points in one shape that select the same closest point in another as their tentative correspondents. The novel algorithm then models the relative weight change over time of a tentative correspondence as the difference between the negative functions of the numbers of points in one shape that actually and ideally select the same closest point in another. Such modeling results in an optimal estimation of the weights of different tentative correspondences, in the sense of deterministic annealing, that lead the camera motion parameters to be estimated in the weighted least squares sense. The proposed algorithm is initialized using the pure translational motion derived from the centroids difference of the overlapping free form shapes being registered. Experimental results show that it outperforms three selected state-of-the-art algorithms on the whole for the accurate and robust registration of real overlapping free form shapes captured using two different laser scanners under typical imaging conditions. en
dc.format.extent 7 en
dc.language.iso eng
dc.relation.ispartof IEEE Transactions on Pattern Analysis and Machine Intelligence en
dc.title Penalizing Closest Point Sharing for Automatic Free Form Shape Registration en
dc.type Text en
dc.type.publicationtype Article (Journal) en
dc.identifier.doi http://dx.doi.org/10.1109/TPAMI.2010.207
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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