Knowledge Commons of Institute of Automation,CAS
Sequential Factorization for Nonrigid Structure from Motion via LBFGS | |
Dong, Qiulei1,3; Hu, Hao2 | |
2016 | |
会议名称 | International Conference on Pattern Recognition |
会议录名称 | Proceedings of International Conference on Pattern Recognition |
会议日期 | December 4-8, 2016 |
会议地点 | Cancún, México |
摘要 | How to implement an effective factorization for nonrigid structure from motion(NRSFM) has attracted much attention in recent years. Addressing this problem, we propose a novel sequential factorization method without extra priors other than the basis low-rank prior, consisting of a motion estimation module and a 3D shape recovery module. In the motion estimation module, for improving the estimation accuracy, a novel objective function is designed for jointly pursuing the Euclidean corrective matrix and the shape coefficient matrix. And an iterative minimization algorithm is explored to solve the designed objective function based on the Limited-memory Broyden-Fletcher-Goldfarb-Shanno approach(LBFGS), naturally leading to the rotation matrix. In the 3D shape recovery module, a simple iterative algorithm is introduced for effectively computing the 3D deformable shapes with the estimated rotation matrix. The proposed extra-prior-free method is easy to implement and it can achieve an effective tradeoff between estimation accuracy and computational speed, since only several classic techniques are involved. Extensive experimental results demonstrate the effectiveness of the proposed method in comparison to five state-of-the-art methods. |
关键词 | Nonrigid Structure From Motion |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/12444 |
专题 | 多模态人工智能系统全国重点实验室_机器人视觉 |
通讯作者 | Dong, Qiulei |
作者单位 | 1.Institute of Automation, Chinese Academy of Sciences 2.Shan Dong University 3.University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Dong, Qiulei,Hu, Hao. Sequential Factorization for Nonrigid Structure from Motion via LBFGS[C],2016. |
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