A Proposal of 3D Feature Based on Occupancy of Point Cloud in Multiscale Shell Region

Shoichi Takei, Shuichi Akizuki, Manabu Hashimoto

    研究成果: Article査読

    抄録

    In this paper, we propose a novel keypoint detection and feature description method called “SHORT” (Shell Histograms and Occupancy from Radial Transform) for fast 3D object recognition. Conventional keypoint detection and feature description methods such as the SHOT method have been necessary to calculate many normal vectors or other statistical values from the point cloud data in local regions, and therefore its computational costs are expensive. By contrast, the SHORT method consists of a fast keypoint detector that does not calculate statistics and a fast feature descriptor that uses a small number of points in the restricted local regions. The keypoint detector uses the occupancy measure which can be estimated by only counting the number of points in multiple spherical shell regions. Also, the feature descriptor uses a small number of points included in distinctive shell regions of multiple scales. Experimental results in 3D object recognition using real dataset show that the processing speed of the proposed method is approximately nine times faster than that of comparative methods.

    本文言語English
    ページ(範囲)54-62
    ページ数9
    ジャーナルElectronics and Communications in Japan
    100
    11
    DOI
    出版ステータスPublished - 2017 11月

    ASJC Scopus subject areas

    • 信号処理
    • 物理学および天文学(全般)
    • コンピュータ ネットワークおよび通信
    • 電子工学および電気工学
    • 応用数学

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