A Person Detection Method Using 3D Laser Scanner – Proposal of Efficient Grouping Method of Point Cloud Data – | Zendy

Kento Hosaka | Zendy; Tetsuo Tomizawa | Zendy

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A Person Detection Method Using 3D Laser Scanner – Proposal of Efficient Grouping Method of Point Cloud Data –

Author(s) -

Kento Hosaka,

Tetsuo Tomizawa

Publication year - 2015

Publication title -

journal of robotics and mechatronics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.257

H-Index - 19

eISSN - 1883-8049

pISSN - 0915-3942

DOI - 10.20965/jrm.2015.p0374

Subject(s) - point cloud , computer vision , computer science , scanner , artificial intelligence , laser scanning , path (computing) , point (geometry) , class (philosophy) , pattern recognition (psychology) , mathematics , laser , physics , geometry , optics , programming language

Our proposed method The purpose of this study is to develop a system for detecting target persons using a 3D laser scanner. The system consists of two parts -- one for grouping and one for determining targets. The grouping part effectively segments individual objects by using two-step grouping. The target part determines target persons for grouping results using shape features. Experimental results showed that our proposed system detects targets as well as existing methods do and that our proposed method performs more quickly than existing methods do.

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