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Optical Engineering

Dense surface reconstruction based on the fusion of monocular vision and three-dimensional flash light detection and ranging
Author(s): Gangtao Hao; Xiaoping Du; Ji-Guang Zhao; Hang Chen; Jianjun Song; Yishuo Song
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Paper Abstract

A dense surface reconstruction approach based on the fusion of monocular vision and three-dimensional (3-D) flash light detection and ranging (LIDAR) is proposed. The texture and geometry information can be obtained simultaneously and quickly for stationary or moving targets with the proposed method. Primarily, our 2-D/3-D fusion imaging system including cameras calibration and an intensity-range image registration algorithm is designed. Subsequently, the adaptive block intensity-range Markov random field (MRF) with optimizing weights is presented to improve the sparse range data from 3-D flash LIDAR. Then the energy function is minimized quickly by conjugate gradient algorithm for each neighborhood system instead of the whole MRF. Finally, the experiments with standard depth datasets and real 2-D/3-D images demonstrate the validity and capability of the proposed scheme.

Paper Details

Date Published: 27 July 2015
PDF: 10 pages
Opt. Eng. 54(7) 073113 doi: 10.1117/1.OE.54.7.073113
Published in: Optical Engineering Volume 54, Issue 7
Show Author Affiliations
Gangtao Hao, The Academy of Equipment Command & Technology (China)
Xiaoping Du, The Academy of Equipment Command & Technology (China)
Ji-Guang Zhao, The Academy of Equipment Command & Technology (China)
Hang Chen, The Academy of Equipment Command & Technology (China)
Jianjun Song, 95806 Troops (China)
Yishuo Song, The Academy of Equipment Command & Technology (China)


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