CASIA OpenIR  > 模式识别国家重点实验室  > 机器人视觉
Sequential Factorization for Nonrigid Structure from Motion via LBFGS
Dong, Qiulei1,3; Hu, Hao2
2016
Conference NameInternational Conference on Pattern Recognition
Source PublicationProceedings of International Conference on Pattern Recognition
Conference DateDecember 4-8, 2016
Conference PlaceCancún, México
AbstractHow 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.
KeywordNonrigid Structure From Motion
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12444
Collection模式识别国家重点实验室_机器人视觉
Corresponding AuthorDong, Qiulei
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.Shan Dong University
3.University of Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Dong, Qiulei,Hu, Hao. Sequential Factorization for Nonrigid Structure from Motion via LBFGS[C],2016.
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