An efficient and accurate method for the relaxation of multiview registration error. |
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Authors: | Sheng-Wen Shih Yao-Tung Chuang Tzu-Yi Yu |
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Affiliation: | Department of Computer Science and Information Engineering, Nationa Chi Nan University, Puli, Nantou, Taiwan, ROC. swshi@ncnu.edu.tw |
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Abstract: | This paper presents a new method for the relaxation of multiview registration error. The multiview registration problem is represented using a graph. Each node and each edge in the graph represents a 3-D data set and a pairwise registration, respectively. Assuming that all the pairwise registration processes have converged to fine results, this paper shows that the multiview registration problem can be converted into a quadratic programming problem of Lie algebra parameters. The constraints are obtained from every cycle of the graph to eliminate the accumulation errors of global registration. A linear solution is proposed to distribute the accumulation error to proper positions in the graph, as specified by the quadratic model. Since the proposed method does not involve the original 3-D data, it has low time and space complexity. Additionally, the proposed method can be embedded into a trust-region algorithm and, thus, can correctly handle the nonlinear effects of large accumulation errors, while preserving the global convergence property to the first-order critical point. Experimental results confirm both the efficiency and the accuracy of the proposed method. |
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