Stereo vision based motion identification

研究成果: Conference contribution

抜粋

The motion identification for a class of movements in the space by using stereo vision is considered by observing at least three points in this paper. The considered motion equation can cover a wide class of practical movements in the space. The observability of this class of movement is clarified. The estimations of the motion parameters which are all time-varying are developed in the proposed algorithm based on the second method of Lyapunov. The assumptions about the perspective system are reasonable, and the convergence conditions are intuitive and have apparently physical interpretations. The proposed recursive algorithm requires minor a priori knowledge about the system and can alleviate the noises in the image data. Furthermore, the proposed algorithm is modified to deal with the occlusion phenomenon. Simulation results show the proposed algorithm is effective even in the presence of measurement noises.

元の言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ575-586
ページ数12
4681 LNCS
出版物ステータスPublished - 2007
イベント3rd International Conference on Intelligent Computing, ICIC 2007 - Qingdao
継続期間: 2007 8 212007 8 24

出版物シリーズ

氏名Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
4681 LNCS
ISSN(印刷物)03029743
ISSN(電子版)16113349

Other

Other3rd International Conference on Intelligent Computing, ICIC 2007
Qingdao
期間07/8/2107/8/24

    フィンガープリント

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

これを引用

Chen, X. (2007). Stereo vision based motion identification. : Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (巻 4681 LNCS, pp. 575-586). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 4681 LNCS).