Shape modeling from multiple view images using GAs

Satoshi Kirihara, Hideo Saito

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Shape modeling is a very important issue for many study, tbr example, object recognition for robot vision, virtual environment construction, and so on. In this paper, a new method of object modeling from multiple view images using genetic algorithms (GAs) is proposed. In this method, a similarity between model and every input image is calculated, and then the model which has the maximum similarity is found. For finding the model of maximum similarity, genetic algorithms are used as the optimization method. In the genetic algorithm, the sharing scheme is employed for efficient detection of multiple solution, because some shape may be represented by multiple shape models. Some results of modeling experiments from real multiple images demonstrate that the proposed method can robustly generate model by using the GA.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages448-454
Number of pages7
Volume1352
ISBN (Print)3540639314, 9783540639312
Publication statusPublished - 1997
Event3rd Asian Conference on Computer Vision, ACCV 1998 - Hong Kong, Hong Kong
Duration: 1998 Jan 81998 Jan 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1352
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd Asian Conference on Computer Vision, ACCV 1998
CountryHong Kong
CityHong Kong
Period98/1/898/1/10

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

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  • Cite this

    Kirihara, S., & Saito, H. (1997). Shape modeling from multiple view images using GAs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1352, pp. 448-454). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1352). Springer Verlag.