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dc.contributor.authorLi, Yue
dc.contributor.authorWang, Bin
dc.contributor.authorGao, Yongsheng
dc.contributor.authorZhou, Jun
dc.contributor.editorLiew, AWC
dc.contributor.editorLovell, B
dc.contributor.editorFookes, C
dc.contributor.editorZhou, J
dc.contributor.editorGao, Y
dc.contributor.editorBlumenstein, M
dc.contributor.editorWang, Z
dc.date.accessioned2018-04-17T01:30:32Z
dc.date.available2018-04-17T01:30:32Z
dc.date.issued2016
dc.identifier.isbn9781509028962
dc.identifier.doi10.1109/DICTA.2016.7797003
dc.identifier.urihttp://hdl.handle.net/10072/124189
dc.description.abstractAffine invariant point-set matching is an important issue in computer vision and pattern recognition. Using reference points derived from the convex hull of the point-set is an existing idea to solve this problem. However, how to choose proper and enough reference points for extracting affine invariant and powerful discriminative descriptors is an open problem. In this paper, a novel method termed convex hull bisection (CHB) is proposed for affine invariant point-set matching. In CHB, for each point in the point-set, two reference points are derived by bisecting the convex hull using the line connecting the point and the centroid of the convex hull. The resulting reference points and other reference points, such as the centroid point of the convex hull and the mean point of the point-set, are utilised to yield an 11-dimensional affine invariant feature vector associated with any point within the point-set. The obtained point based descriptors are used for point-set matching. The proposed method works well even in the case that reference points are overlapping or collinear, which overcomes the limitations of the existing convex hull based methods. The effectiveness of the proposed method is validated by an extensive experimental investigation.
dc.description.peerreviewedYes
dc.languageEnglish
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.publisher.placeAustralia
dc.relation.ispartofconferencenameInternational Conference on Digital Image Computing - Techniques and Applications (DICTA)
dc.relation.ispartofconferencetitle2016 INTERNATIONAL CONFERENCE ON DIGITAL IMAGE COMPUTING: TECHNIQUES AND APPLICATIONS (DICTA)
dc.relation.ispartofdatefrom2016-11-30
dc.relation.ispartofdateto2016-12-02
dc.relation.ispartoflocationGold Coast, AUSTRALIA
dc.relation.ispartofpagefrom524
dc.relation.ispartofpagefrom8 pages
dc.relation.ispartofpageto531
dc.relation.ispartofpageto8 pages
dc.subject.fieldofresearchComputer Vision
dc.subject.fieldofresearchcode080104
dc.titleAffine invariant point-set matching using convex hull bisection
dc.typeConference output
dc.type.descriptionE1 - Conferences
dc.type.codeE - Conference Publications
dc.description.versionPost-print
gro.facultyGriffith Sciences, School of Engineering and Built Environment
gro.rights.copyright© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorGao, Yongsheng
gro.griffith.authorWang, Bin
gro.griffith.authorZhou, Jun
gro.griffith.authorLi, Yue


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