Robust dense reconstruction by range merging based on confidence estimation

ISCAS OpenIR

	Robust dense reconstruction by range merging based on confidence estimation
	Chen, YD; Hao, CY; Wu, W; Wu, EH
	2016
发表期刊	SCIENCE CHINA-INFORMATION SCIENCES
ISSN	1674-733X
卷号	59 期号:9
摘要	Although the stereo matching problem has been extensively studied during the past decades, automatically computing a dense 3D reconstruction from several multiple views is still a difficult task owing to the problems of textureless regions, outliers, detail loss, and various other factors. In this paper, these difficult problems are handled effectively by a robust model that outputs an accurate and dense reconstruction as the final result from an input of multiple images captured by a normal camera. First, the positions of the camera and sparse 3D points are estimated by a structure-from-motion algorithm and we compute the range map with a confidence estimation for each image in our approach. Then all the range maps are integrated into a fine point cloud data set. In the final step we use a Poisson reconstruction algorithm to finish the reconstruction. The major contributions of the work lie in the following points: effective range-computation and confidence-estimation methods are proposed to handle the problems of textureless regions, outliers and detail loss. Then, the range maps are merged into the point cloud data in terms of a confidence-estimation. Finally, Poisson reconstruction algorithm completes the dense mesh. In addition, texture mapping is also implemented as a post-processing work for obtaining good visual effects. Experimental results are presented to demonstrate the effectiveness of the proposed approach.; Although the stereo matching problem has been extensively studied during the past decades, automatically computing a dense 3D reconstruction from several multiple views is still a difficult task owing to the problems of textureless regions, outliers, detail loss, and various other factors. In this paper, these difficult problems are handled effectively by a robust model that outputs an accurate and dense reconstruction as the final result from an input of multiple images captured by a normal camera. First, the positions of the camera and sparse 3D points are estimated by a structure-from-motion algorithm and we compute the range map with a confidence estimation for each image in our approach. Then all the range maps are integrated into a fine point cloud data set. In the final step we use a Poisson reconstruction algorithm to finish the reconstruction. The major contributions of the work lie in the following points: effective range-computation and confidence-estimation methods are proposed to handle the problems of textureless regions, outliers and detail loss. Then, the range maps are merged into the point cloud data in terms of a confidence-estimation. Finally, Poisson reconstruction algorithm completes the dense mesh. In addition, texture mapping is also implemented as a post-processing work for obtaining good visual effects. Experimental results are presented to demonstrate the effectiveness of the proposed approach.
收录类别	SCI
关键词	Stereo Matching 3d Reconstruction Textureless Regions Outliers Details Loss Range Map
部门归属	Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China. Nanjing Univ Posts & Telecommun, Sch Educ Sci & Technol, Nanjing 210023, Jiangsu, Peoples R China. Univ Macau, Dept Comp & Informat Sci, Fac Sci & Technol, Macau 999078, Peoples R China. Chinese Acad Sci, Inst Software, State Key Lab Comp Sci, Beijing 100864, Peoples R China.
语种	英语
WOS记录号	WOS:000381929800002
引用统计
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/17301
专题	中国科学院软件研究所
推荐引用方式 GB/T 7714	Chen, YD,Hao, CY,Wu, W,et al. Robust dense reconstruction by range merging based on confidence estimation[J]. SCIENCE CHINA-INFORMATION SCIENCES,2016,59(9).
APA	Chen, YD,Hao, CY,Wu, W,&Wu, EH.(2016).Robust dense reconstruction by range merging based on confidence estimation.SCIENCE CHINA-INFORMATION SCIENCES,59(9).
MLA	Chen, YD,et al."Robust dense reconstruction by range merging based on confidence estimation".SCIENCE CHINA-INFORMATION SCIENCES 59.9(2016).

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