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		<citationkey>CabreraOrtiGonç:2018:ToMeCo</citationkey>
		<title>Towards a metric for computing similarity ofrestricted non-rigid objects in real time</title>
		<format>On-line</format>
		<year>2018</year>
		<date>Oct. 29 - Nov. 1, 2018</date>
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		<author>Cabrera, Elizabeth V,</author>
		<author>Ortiz, Luis E.,</author>
		<author>Gonçalves, Luiz M.,</author>
		<affiliation>Universidad Federal do Rio Grande do Norte</affiliation>
		<affiliation>Universidad Federal do Rio Grande do Norte</affiliation>
		<affiliation>Universidad Federal do Rio Grande do Norte</affiliation>
		<editor>Ross, Arun,</editor>
		<editor>Gastal, Eduardo S. L.,</editor>
		<editor>Jorge, Joaquim A.,</editor>
		<editor>Queiroz, Ricardo L. de,</editor>
		<editor>Minetto, Rodrigo,</editor>
		<editor>Sarkar, Sudeep,</editor>
		<editor>Papa, João Paulo,</editor>
		<editor>Oliveira, Manuel M.,</editor>
		<editor>Arbeláez, Pablo,</editor>
		<editor>Mery, Domingo,</editor>
		<editor>Oliveira, Maria Cristina Ferreira de,</editor>
		<editor>Spina, Thiago Vallin,</editor>
		<editor>Mendes, Caroline Mazetto,</editor>
		<editor>Costa, Henrique Sérgio Gutierrez,</editor>
		<editor>Mejail, Marta Estela,</editor>
		<editor>Geus, Klaus de,</editor>
		<editor>Scheer, Sergio,</editor>
		<e-mailaddress>vcabrera@dca.ufrn.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 31 (SIBGRAPI)</conferencename>
		<conferencelocation>Foz do Iguaçu, PR, Brazil</conferencelocation>
		<booktitle>Proceedings</booktitle>
		<publisher>Sociedade Brasileira de Computação</publisher>
		<publisheraddress>Porto Alegre</publisheraddress>
		<documentstage>not transferred</documentstage>
		<transferableflag>1</transferableflag>
		<tertiarytype>Master's or Doctoral Work</tertiarytype>
		<keywords>similarity, non-rigid objects, restricted deformation, point clouds, Mahalanobis distance, Hausdorf distance, real time.</keywords>
		<abstract>We propose an approach towards measuring the similarity of restricted deformable objects using three-dimensional point clouds of them. Basically, given the point clouds of the object in the ideal and deformed postures, object part labeling is performed based on RGB to find a first segmentation of the object cloud in parts. Then two methods are tested for measuring similarity of each partial clouds set, with verification of their precision and time: the computation of Mahalanobis distances and of the Hausdorff distances of the point clouds, the last after registration and alignment of them. Experimental results show a faster execution time of the Mahalanobis metric, in despite of its lower precision in similarity estimation. Several applications in computer graphics and virtual reality can rely on such result in order to determine levels of deformation of articulated or restricted deformable objects.</abstract>
		<language>en</language>
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		<usergroup>vcabrera@dca.ufrn.br</usergroup>
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