Large-Scale bundle adjustment by parameter vector partition
作者： Shanmin Pang , Jianrue Xue , Le Wang , Nanning Zheng
DOI: 10.1007/978-3-642-37447-0_3
关键词:
摘要: We propose an efficient parallel bundle adjustment (BA) algorithm to refine 3D reconstruction of the large-scale structure from motion (SfM) problem, which uses image collections Internet. Different latest BA techniques that improve efficiency by optimizing reprojection error function with Conjugate Gradient (CG) methods, we employ parameter vector partition strategy. More specifically, whole into a set individual sub-vectors via normalized cut (Ncut). Correspondingly, solution problem can be obtained minimizing subproblems on these sub-vector spaces. Our approach is approximately parallel, and there no need solve linear equation problem. Experiments carried out low-end computer 4GB RAM demonstrate accuracy proposed algorithm.
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