Physical reasoning for 3D object recognition using global hypothesis verification

Shuichi Akizuki, Manabu Hashimoto

研究成果: Conference contribution

2 引用 (Scopus)

抜粋

In this paper, we propose a method to recognize the 6DoF pose of multiple objects simultaneously. One good solution to recognize them is applying a Hypothesis Verification (HV) algorithm. This type of algorithm evaluates consistency between an input scene and scene hypotheses represented by combinations of object candidates generated from the model based matching. Its use achieves reliable recognition because it maximizes the fitting score between the input scene and the scene hypotheses instead of maximizing the fitting score of an object candidate. We have developed a more reliable HV algorithm that uses a novel cue, the naturalness of an object’s layout (its physical reasoning). This cue evaluates whether the object’s layout in a scene hypothesis can actually be achieved by using simple collision detection. Experimental results show that using the physical reasoning have improved recognition reliability.

元の言語English
ホスト出版物のタイトルComputer Vision – ECCV 2016 Workshops, Proceedings
出版者Springer Verlag
ページ595-605
ページ数11
9915 LNCS
ISBN(印刷物)9783319494081
DOI
出版物ステータスPublished - 2016
外部発表Yes
イベント14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
継続期間: 2016 10 82016 10 16

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)
9915 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

Other

Other14th European Conference on Computer Vision, ECCV 2016
Netherlands
Amsterdam
期間16/10/816/10/16

    フィンガープリント

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

これを引用

Akizuki, S., & Hashimoto, M. (2016). Physical reasoning for 3D object recognition using global hypothesis verification. : Computer Vision – ECCV 2016 Workshops, Proceedings (巻 9915 LNCS, pp. 595-605). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻 9915 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-49409-8_51