Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.imavis.2006.07.006
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dc.title3D registration of partially overlapping surfaces using a volumetric approach
dc.contributor.authorXiao, G.
dc.contributor.authorOng, S.H.
dc.contributor.authorFoong, K.W.C.
dc.date.accessioned2014-06-16T09:22:57Z
dc.date.available2014-06-16T09:22:57Z
dc.date.issued2007-06-01
dc.identifier.citationXiao, G., Ong, S.H., Foong, K.W.C. (2007-06-01). 3D registration of partially overlapping surfaces using a volumetric approach. Image and Vision Computing 25 (6) : 934-944. ScholarBank@NUS Repository. https://doi.org/10.1016/j.imavis.2006.07.006
dc.identifier.issn02628856
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/53868
dc.description.abstractA novel volumetric approach for the 3D registration of a generic crown and a complete tooth of the same tooth type is presented. Unlike most existing 3D partial surface registration methods, our algorithm does not require the two surfaces to be instances of the same object, only that they are of the same class (i.e., a group of similar objects). The Euclidean distance fields of the two surfaces are computed, and a set of distance vectors within these distance fields are used to generate a series of candidate transformations. By verifying the set of candidate parameters, the one resulting in the smallest registration error is chosen as the optimal solution. An additional advantage of our algorithm is that initial pose estimation is not required. Its effectiveness is confirmed by a series of experiments. © 2006 Elsevier B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/j.imavis.2006.07.006
dc.sourceScopus
dc.subject3D registration
dc.subjectEuclidean distance field
dc.subjectPartially overlapping surface
dc.subjectVolumetric
dc.typeArticle
dc.contributor.departmentPREVENTIVE DENTISTRY
dc.contributor.departmentELECTRICAL & COMPUTER ENGINEERING
dc.description.doi10.1016/j.imavis.2006.07.006
dc.description.sourcetitleImage and Vision Computing
dc.description.volume25
dc.description.issue6
dc.description.page934-944
dc.description.codenIVCOD
dc.identifier.isiut000246538600015
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