TY - GEN
T1 - Simultaneous Correspondences Estimation and Non-Rigid Structure Reconstruction
AU - Dai, Yuchao
AU - Li, Hongdong
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/22
Y1 - 2016/12/22
N2 - Given multi-view correspondences, it has been shown that 3D non-rigid structure can be recovered through factorization based techniques. However, establishing reliable correspondences across multi-view images of non-rigid structure is not an easy task. Existing methods solve multi-view correspondences and 3D non-rigid structure in sequel, which cannot exploit the crossover constraints in each sub-problem (\ie, constraints in non-rigid structure has not been enforced in establishing multi-view correspondences and verse vise). In this paper, we present a unified framework to simultaneously solve for multi-view correspondences and non-rigid structure. We formulate the problem by using the Partial Permutation Matrices (PPMs) and aim at establishing multi-view correspondences while simultaneously enforcing the low-rank constraint in non-rigid structure deformation. Additionally, our method can handle outliers and missing data elegantly under the same framework. We solve the simultaneous non-rigid structure and correspondences recovery problem via the Alternating Direction Method of Multipliers (ADMM). Experimental results on both synthetic and real images show that the proposed method achieves state-of-the-art performance on both sparse and dense non-rigid reconstruction problems.
AB - Given multi-view correspondences, it has been shown that 3D non-rigid structure can be recovered through factorization based techniques. However, establishing reliable correspondences across multi-view images of non-rigid structure is not an easy task. Existing methods solve multi-view correspondences and 3D non-rigid structure in sequel, which cannot exploit the crossover constraints in each sub-problem (\ie, constraints in non-rigid structure has not been enforced in establishing multi-view correspondences and verse vise). In this paper, we present a unified framework to simultaneously solve for multi-view correspondences and non-rigid structure. We formulate the problem by using the Partial Permutation Matrices (PPMs) and aim at establishing multi-view correspondences while simultaneously enforcing the low-rank constraint in non-rigid structure deformation. Additionally, our method can handle outliers and missing data elegantly under the same framework. We solve the simultaneous non-rigid structure and correspondences recovery problem via the Alternating Direction Method of Multipliers (ADMM). Experimental results on both synthetic and real images show that the proposed method achieves state-of-the-art performance on both sparse and dense non-rigid reconstruction problems.
UR - http://www.scopus.com/inward/record.url?scp=85011103068&partnerID=8YFLogxK
U2 - 10.1109/DICTA.2016.7797083
DO - 10.1109/DICTA.2016.7797083
M3 - Conference contribution
T3 - 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
BT - 2016 International Conference on Digital Image Computing
A2 - Liew, Alan Wee-Chung
A2 - Zhou, Jun
A2 - Gao, Yongsheng
A2 - Wang, Zhiyong
A2 - Fookes, Clinton
A2 - Lovell, Brian
A2 - Blumenstein, Michael
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
Y2 - 30 November 2016 through 2 December 2016
ER -