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Robust dense reconstruction by range merging based on confidence estimation
Yadang CHEN1,3; Chuanyan HAO2,3; Wen WU3; Enhua WU4
2016
Source PublicationScience China Information Sciences
ISSN1674-733X
Volume59Issue:9
Abstract

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. © 2016, Science China Press and Springer-Verlag Berlin Heidelberg.

Keyword3d Reconstruction Details Loss Outliers Range Map Stereo Matching Textureless Regions
DOI10.1007/s11432-015-0957-4
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic
WOS IDWOS:000381929800002
The Source to ArticleScopus
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Cited Times [WOS]:57   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Faculty of Science and Technology
Corresponding AuthorChuanyan HAO
Affiliation1.School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.School of Education Science and Technology, Nanjing University of Posts and Telecommunications, Nanjing 210023, China;
3.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau 999078, China;
4.State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100864, China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Yadang CHEN,Chuanyan HAO,Wen WU,et al. Robust dense reconstruction by range merging based on confidence estimation[J]. Science China Information Sciences,2016,59(9).
APA Yadang CHEN,Chuanyan HAO,Wen WU,&Enhua WU.(2016).Robust dense reconstruction by range merging based on confidence estimation.Science China Information Sciences,59(9).
MLA Yadang CHEN,et al."Robust dense reconstruction by range merging based on confidence estimation".Science China Information Sciences 59.9(2016).
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