A Robust Error-Resistant View Selection Method for 3D Reconstruction
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arXiv
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| Auteurs principaux: | , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910343003897856 |
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| author | Zhang, Shaojie Wang, Yinghui Nan, Bin Li, Wei Yang, Jinlong Yan, Tao Wang, Yukai Huang, Liangyi Wang, Mingfeng Atadjanov, Ibragim R. |
| author_facet | Zhang, Shaojie Wang, Yinghui Nan, Bin Li, Wei Yang, Jinlong Yan, Tao Wang, Yukai Huang, Liangyi Wang, Mingfeng Atadjanov, Ibragim R. |
| contents | To address the issue of increased triangulation uncertainty caused by selecting views with small camera baselines in Structure from Motion (SFM) view selection, this paper proposes a robust error-resistant view selection method. The method utilizes a triangulation-based computation to obtain an error-resistant model, which is then used to construct an error-resistant matrix. The sorting results of each row in the error-resistant matrix determine the candidate view set for each view. By traversing the candidate view sets of all views and completing the missing views based on the error-resistant matrix, the integrity of 3D reconstruction is ensured. Experimental comparisons between this method and the exhaustive method with the highest accuracy in the COLMAP program are conducted in terms of average reprojection error and absolute trajectory error in the reconstruction results. The proposed method demonstrates an average reduction of 29.40% in reprojection error accuracy and 5.07% in absolute trajectory error on the TUM dataset and DTU dataset. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_11431 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | A Robust Error-Resistant View Selection Method for 3D Reconstruction Zhang, Shaojie Wang, Yinghui Nan, Bin Li, Wei Yang, Jinlong Yan, Tao Wang, Yukai Huang, Liangyi Wang, Mingfeng Atadjanov, Ibragim R. Computer Vision and Pattern Recognition To address the issue of increased triangulation uncertainty caused by selecting views with small camera baselines in Structure from Motion (SFM) view selection, this paper proposes a robust error-resistant view selection method. The method utilizes a triangulation-based computation to obtain an error-resistant model, which is then used to construct an error-resistant matrix. The sorting results of each row in the error-resistant matrix determine the candidate view set for each view. By traversing the candidate view sets of all views and completing the missing views based on the error-resistant matrix, the integrity of 3D reconstruction is ensured. Experimental comparisons between this method and the exhaustive method with the highest accuracy in the COLMAP program are conducted in terms of average reprojection error and absolute trajectory error in the reconstruction results. The proposed method demonstrates an average reduction of 29.40% in reprojection error accuracy and 5.07% in absolute trajectory error on the TUM dataset and DTU dataset. |
| title | A Robust Error-Resistant View Selection Method for 3D Reconstruction |
| topic | Computer Vision and Pattern Recognition |
| url | https://arxiv.org/abs/2402.11431 |