A shape distribution for comparing 3D models

Levi C. Monteverde, Conrado R. Ruiz, Zhiyong Huang

Research output: Book chapterConference contributionpeer-review

9 Citations (Scopus)

Abstract

This study developed a new shape-based 3D model descriptor based on the D2 shape descriptor developed by Osada, et al of Princeton University. Shape descriptors can be used to measure dissimilarity between two 3D models. In this work, we advance it by proposing a novel descriptor D2a. In our method, N pairs of faces are randomly chosen from a 3D model, with probability proportional to the area of the face. The ratio of the smaller area over the larger area is computed and its frequency stored, generating a frequency distribution of N ratios which is stored as the second dimension of a 2D array, while the first dimension contains the frequency distribution of distances of randomly generated point pairs (the D2 distribution). The resulting descriptor, D2a, is a two-dimensional histogram that incorporates two shape features: The ratio of face areas and the distance between two random points.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 13th International Multimedia Modeling Conference, MMM 2007, Proceedings
Pages54-63
Number of pages10
EditionPART 1
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event13th International Multimedia Modeling Conference, MMM 2007 - Singapore, Singapore
Duration: 9 Jan 200712 Jan 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume4351 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Multimedia Modeling Conference, MMM 2007
Country/TerritorySingapore
CitySingapore
Period9/01/0712/01/07

Fingerprint

Dive into the research topics of 'A shape distribution for comparing 3D models'. Together they form a unique fingerprint.

Cite this