TY - GEN
T1 - Large-scale bundle adjustment by parameter vector partition
AU - Pang, Shanmin
AU - Xue, Jianrue
AU - Wang, Le
AU - Zheng, Nanning
PY - 2012
Y1 - 2012
N2 - 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 from Internet. Different from the latest BA techniques that improve efficiency by optimizing the reprojection error function with Conjugate Gradient (CG) methods, we employ the parameter vector partition strategy. More specifically, we partition the whole BA parameter vector into a set of individual sub-vectors via normalized cut (Ncut). Correspondingly, the solution of the BA problem can be obtained by minimizing subproblems on these sub-vector spaces. Our approach is approximately parallel, and there is no need to solve the large-scale linear equation of the BA problem. Experiments carried out on a low-end computer with 4GB RAM demonstrate the efficiency and accuracy of the proposed algorithm.
AB - 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 from Internet. Different from the latest BA techniques that improve efficiency by optimizing the reprojection error function with Conjugate Gradient (CG) methods, we employ the parameter vector partition strategy. More specifically, we partition the whole BA parameter vector into a set of individual sub-vectors via normalized cut (Ncut). Correspondingly, the solution of the BA problem can be obtained by minimizing subproblems on these sub-vector spaces. Our approach is approximately parallel, and there is no need to solve the large-scale linear equation of the BA problem. Experiments carried out on a low-end computer with 4GB RAM demonstrate the efficiency and accuracy of the proposed algorithm.
UR - https://www.scopus.com/pages/publications/84875885452
U2 - 10.1007/978-3-642-37447-0_3
DO - 10.1007/978-3-642-37447-0_3
M3 - 会议稿件
AN - SCOPUS:84875885452
SN - 9783642374463
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 26
EP - 39
BT - Computer Vision, ACCV 2012 - 11th Asian Conference on Computer Vision, Revised Selected Papers
T2 - 11th Asian Conference on Computer Vision, ACCV 2012
Y2 - 5 November 2012 through 9 November 2012
ER -