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dc.contributor.convenorAndrew Bradleyen_US
dc.contributor.authorZhang, Paulen_US
dc.contributor.authorGao, Yongshengen_US
dc.contributor.editorIEEEen_US
dc.date.accessioned2017-04-24T12:26:38Z
dc.date.available2017-04-24T12:26:38Z
dc.date.issued2011en_US
dc.date.modified2012-02-16T05:28:49Z
dc.identifier.refurihttp://itee.uq.edu.au/~dicta2011/en_US
dc.identifier.doi10.1109/DICTA.2011.106en_US
dc.identifier.urihttp://hdl.handle.net/10072/42759
dc.description.abstractMeasuring the similarity between articulated shapes is a fundamental yet challenging problem. This paper proposes a novel shape descriptor based on Width Distributions (WD), which is robust to articulations. We show that the width distributions are articulation insensitive yet descriptive to distinguish different shapes with varied part structures. With measurements on distributions only, the proposed method does not require any alignment between two objects and thus is more robust than correspondence-based measurements. First, the medial axes of the objects are extracted and fitted to B-Splines to remove outliners. The width of the object shape perpendicular to the medial axis can be calculated for each position on the medial axis. The histograms of those widths are compared using chisquare method for similarity. Experiments on standard 2D shape database show that the proposed method performed better than standard shape distribution algorithms and similarly to other articulation-robust shape descriptors, such as inner-distance. The speed of the proposed method is much faster than the more sophisticated inner-distance, as the proposed method is much simpler in nature and requires limited image processing and pattern classification. These results suggested it could be an efficient and effective method to describe and to match articulated shapes.en_US
dc.description.peerreviewedYesen_US
dc.description.publicationstatusYesen_US
dc.format.extent279887 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglishen_US
dc.publisherIEEE Computer Societyen_US
dc.publisher.placeLos Alamitos, CA, USAen_US
dc.relation.ispartofstudentpublicationNen_US
dc.relation.ispartofconferencename2011 International Conference on Digital Image Computing: Techniques and Applications (DICTA 2011)en_US
dc.relation.ispartofconferencetitleProceedings - 2011 International Conference on Digital Image Computing: Techniques and Applications DICTA 2011en_US
dc.relation.ispartofdatefrom2011-12-06en_US
dc.relation.ispartofdateto2011-12-08en_US
dc.relation.ispartoflocationNoosa, Queensland, Australiaen_US
dc.rights.retentionYen_US
dc.subject.fieldofresearchComputer Visionen_US
dc.subject.fieldofresearchcode080104en_US
dc.titleWidth Distributions for Shape Descriptionen_US
dc.typeConference outputen_US
dc.type.descriptionE1 - Conference Publications (HERDC)en_US
dc.type.codeE - Conference Publicationsen_US
gro.facultyGriffith Sciences, Griffith School of Engineeringen_US
gro.rights.copyrightCopyright 2011 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.en_US
gro.date.issued2011
gro.hasfulltextFull Text


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    Contains papers delivered by Griffith authors at national and international conferences.

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