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Shape matching and recognition using a physically based object model

dc.citation.epage222en_US
dc.citation.issue2en_US
dc.citation.spage211en_US
dc.citation.volume25en_US
dc.citation.woscount2
dc.contributor.authorChuang, JHen_US
dc.contributor.authorSheu, JFen_US
dc.contributor.authorLin, CCen_US
dc.contributor.authorYang, HKen_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.date.accessioned2014-12-08T15:43:58Z
dc.date.available2014-12-08T15:43:58Z
dc.date.issued2001-04-01en_US
dc.description.abstractWe present a novel approach of shape matching and recognition of 3D objects using artificial potential fields. The potential model assumes that boundary of every 3D template object of identical Volume is uniformly charged. An initially small input object placed inside a template object will experience repulsive force and torque arising from the potential field. A better match in shape between the template object and the input object can be obtained if the input object translates and reorients itself to reduce the potential while growing in size. The template object which allows the maximum growth of the input object corresponds to the best match and thus represents the shape of the input object. The above repulsive force and torque are analytically tractable for an input object represented by its boundary samples. which makes the shape matching efficient. The proposed approach is intrinsically invariant under translation: rotation and size changes of the input object. (C) 2001 Elsevier Science Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/S0097-8493(00)00125-4en_US
dc.identifier.issn0097-8493en_US
dc.identifier.journalCOMPUTERS & GRAPHICS-UKen_US
dc.identifier.urihttp://dx.doi.org/10.1016/S0097-8493(00)00125-4en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/29730
dc.identifier.wosnumberWOS:000168177200003
dc.language.isoen_USen_US
dc.subjectshape orientationen_US
dc.subjectshape matchingen_US
dc.subjectobject recognitionen_US
dc.subjectartificial potential fielden_US
dc.titleShape matching and recognition using a physically based object modelen_US
dc.typeArticleen_US

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