Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Active Appearance Models Revisited
International Journal of Computer Vision
A Direct Method for 3D Factorization of Nonrigid Motion Observed in 2D
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Quasiconvex Optimization for Robust Geometric Reconstruction
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Multiple View Geometry and the L_"-norm
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Uncalibrated Perspective Reconstruction of Deformable Structures
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Removing Outliers Using The L\infty Norm
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Nonrigid Structure-from-Motion: Estimating Shape and Motion with Hierarchical Priors
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Effective Approach to 3D Deformable Surface Tracking
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part III
The painful face - Pain expression recognition using active appearance models
Image and Vision Computing
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Nonrigid reconstruction plays an important role in many applications like image-based modeling, human-computer interaction. In this paper, we propose an effective approach for 3D non-rigid structure reconstruction using linear programming from an image pair taken with a stereo rig. In contrast to previous approaches, the proposed method neither involves smoothness constraints nor need prior knowledge between consecutive frames, which enables us to recover shapes of surfaces with smooth, sharp and other complex deformations from a single image pair. Specifically, we model the surface as a triangulated mesh and formulate the reconstruction problem as a Linear Programming (LP) problem using L∞ that can be effectively solved. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which preserve original lengths of mesh edges. The robustness and accuracy of our approach are evaluated quantitatively on synthetic data and on real data.