3-D feature point matching for object recognition based on estimation of local shape distinctiveness

Masanobu Nagase, Shuichi Akizuki, Manabu Hashimoto

    研究成果: Conference contribution

    5 被引用数 (Scopus)

    抄録

    In this paper, we propose a reliable 3-D object recognition method that can statistically minimize object mismatching. Our method basically uses a 3-D object model that is represented as a set of feature points with 3-D coordinates. Each feature point also has an attribute value for the local shape around the point. The attribute value is represented as an orientation histogram of a normal vector calculated by using several neighboring feature points around each point. Here, the important thing is this attribute value means its local shape. By estimating the relative similarity of two points of all possible combinations in the model, we define the distinctiveness of each point. In the proposed method, only a small number of distinctive feature points are selected and used for matching with all feature points extracted from an acquired range image. Finally, the position and pose of the target object can be estimated from a number of correctly matched points. Experimental results using actual scenes have demonstrated that the recognition rate of our method is 93.8%, which is 42.2% higher than that of the conventional Spin Image method. Furthermore, its computing time is about nine times faster than that of the Spin Image method.

    本文言語English
    ホスト出版物のタイトルComputer Analysis of Images and Patterns - 15th International Conference, CAIP 2013, Proceedings
    ページ473-481
    ページ数9
    PART 1
    DOI
    出版ステータスPublished - 2013 9 26
    イベント15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013 - York, United Kingdom
    継続期間: 2013 8 272013 8 29

    出版物シリーズ

    名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    番号PART 1
    8047 LNCS
    ISSN(印刷版)0302-9743
    ISSN(電子版)1611-3349

    Other

    Other15th International Conference on Computer Analysis of Images and Patterns, CAIP 2013
    国/地域United Kingdom
    CityYork
    Period13/8/2713/8/29

    ASJC Scopus subject areas

    • 理論的コンピュータサイエンス
    • コンピュータ サイエンス(全般)

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