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| Robust dense reconstruction by range merging based on confidence estimation | |
| Chen, YD; Hao, CY; Wu, W; Wu, EH | |
| 2016 | |
| Source | SCIENCE CHINA-INFORMATION SCIENCES
 |
| ISSN | 1674-733X |
| Volume | 59Issue:9 |
| English 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.; 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. |
| Indexed Type | SCI |
| Keyword | Stereo Matching 3d Reconstruction Textureless Regions Outliers Details Loss Range Map |
| Department | 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. |
| Language | 英语 |
| WOS ID | WOS:000381929800002 |
| Citation statistics | |
| Content Type | 期刊论文 |
| URI | http://ir.iscas.ac.cn/handle/311060/17301 |
| Collection | 中国科学院软件研究所 |
| Recommended Citation 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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