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Reference TypeConference Proceedings
Last Update2018:
Metadata Last Update2020: administrator
Citation KeyCabreraAvilaOrtiGonç:2018:ToMeCo
TitleTowards a metric for computing similarity ofrestricted non-rigid objects in real time
DateOct. 29 - Nov. 1, 2018
Access Date2020, Dec. 04
Number of Files1
Size1431 KiB
Context area
Author1 Cabrera Avila, Elizabeth Viviana
2 Ortiz Fernández, Luis Enrique
3 Gonçalves Garcia, Luiz Marcos.
Affiliation1 Universidad Federal do Rio Grande do Norte
2 Universidad Federal do Rio Grande do Norte
3 Universidad Federal do Rio Grande do Norte
EditorRoss, Arun
Gastal, Eduardo S. L.
Jorge, Joaquim A.
Queiroz, Ricardo L. de
Minetto, Rodrigo
Sarkar, Sudeep
Papa, João Paulo
Oliveira, Manuel M.
Arbeláez, Pablo
Mery, Domingo
Oliveira, Maria Cristina Ferreira de
Spina, Thiago Vallin
Mendes, Caroline Mazetto
Costa, Henrique Sérgio Gutierrez
Mejail, Marta Estela
Geus, Klaus de
Scheer, Sergio
Conference NameConference on Graphics, Patterns and Images, 31 (SIBGRAPI)
Conference LocationFoz do Iguaçu, PR, Brazil
Book TitleProceedings
PublisherSociedade Brasileira de Computação
Publisher CityPorto Alegre
History2018-10-23 19:07:54 :: -> administrator :: 2018
2020-02-20 22:06:51 :: administrator -> :: 2018
Content and structure area
Is the master or a copy?is the master
Document Stagecompleted
Document Stagenot transferred
Tertiary TypeMaster's or Doctoral Work
Keywordssimilarity, non-rigid objects, restricted deformation, point clouds, Mahalanobis distance, Hausdorf distance, real time.
AbstractWe 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.
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