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Proceedings Paper

A portable low-cost 3D point cloud acquiring method based on structure light
Author(s): Li Gui; Shunyi Zheng; Xia Huang; Like Zhao; Hao Ma; Chao Ge; Qiuxia Tang
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Paper Abstract

A fast and low-cost method of acquiring 3D point cloud data is proposed in this paper, which can solve the problems of lack of texture information and low efficiency of acquiring point cloud data with only one pair of cheap cameras and projector. Firstly, we put forward a scene adaptive design method of random encoding pattern, that is, a coding pattern is projected onto the target surface in order to form texture information, which is favorable for image matching. Subsequently, we design an efficient dense matching algorithm that fits the projected texture. After the optimization of global algorithm and multi-kernel parallel development with the fusion of hardware and software, a fast acquisition system of point-cloud data is accomplished. Through the evaluation of point cloud accuracy, the results show that point cloud acquired by the method proposed in this paper has higher precision. What`s more, the scanning speed meets the demand of dynamic occasion and has better practical application value.

Paper Details

Date Published: 8 March 2018
PDF: 7 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106091M (8 March 2018); doi: 10.1117/12.2288328
Show Author Affiliations
Li Gui, Wuhan Univ. (China)
Shunyi Zheng, Wuhan Univ. (China)
Xia Huang, Wuhan Univ. (China)
Like Zhao, Wuhan Univ. (China)
Hao Ma, Wuhan Univ. (China)
Chao Ge, Wuhan Univ. (China)
Qiuxia Tang, HuBei Urban and Rural Planning Ctr. (China)


Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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