图像三维重建下视差角与笛卡尔参数化的光束法平差收敛性对比OA

To address the problems of limited-scale comparative experiments against mainstream approaches and inconsistent optimizer configurations when applying parallax-angle parameterization to image-based 3D reconstruc-tion,106 bundle adjustment(BA)datasets were constructed spanning vehicle-borne,UAV,and close-range scenarios.We standardized the solution workflows for the mainstream Cartesian-coordinate parameterization(SBA)and parallax-angle parameterization(PBA)methods to ensure a fair comparison.The two methods were systematically evaluated in terms of convergence,computational time,image-space accuracy,and parameter-space accuracy.The experimental results showed that,across the 106 paired datasets,PBA generally required significantly fewer iterations than SBA,exhibiting a faster convergence trend.In representative scenarios with relatively large initial point-cloud noise or divergence of the Cartesian-coordinate method,PBA yielded more stable optimization results in both image and parameter spaces.The datasets and source code are publicly available at https://reurl.cc/OmZz09 and https://github.com/Polar-vision/PBA-V3.