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A Robust Error-Resistant View Selection Method for 3D Reconstruction

Shaojie ZhangSchool of Artificial Intelligence and Computer Science , Jiangnan University , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaYinghui WangEngineering Research Center of Intelligent Technology for Healthcare , Ministry of Education , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaNan, BinSchool of Artificial Intelligence and Computer Science , Jiangnan University , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaLi, WeiSchool of Artificial Intelligence and Computer Science , Jiangnan University , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaJinlong YangSchool of Artificial Intelligence and Computer Science , Jiangnan University , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaYan, TaoSchool of Artificial Intelligence and Computer Science , Jiangnan University , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaWang, YukaiEngineering Research Center of Intelligent Technology for Healthcare , Ministry of Education , 1800 Li Lake Avenue , wuxi , 214122 , Jiangsu , PR ChinaLiangyi HuangSchool of Computing and Augmented Intelligence , Arizona State University , 1151 S Forest Ave , Tempe , 8528 , AZ , U.SMingfeng WangDepartment of Mechanical and Aerospace Engineering , Brunel University , Kingston Lane , London , UB8 3PH , Middlesex , U.KAtadjanov, Ibragim R.Tashkent University of Information Technologies named after al-Khwarizmi , 108 Amir Temur Avenue , Tashkent , 100084 , , Uzbekistan

2024en

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ABI

Annotatsiya

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.

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DOI: 10.48550/arxiv.2402.11431

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