Efficient large-scale stereo matching
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Multiview face capture using polarized spherical gradient illumination
Proceedings of the 2011 SIGGRAPH Asia Conference
Curvature regularization for curves and surfaces in a global optimization framework
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
International Journal of Computer Vision
An optimal time---space algorithm for dense stereo matching
Journal of Real-Time Image Processing
Discrete Applied Mathematics
Approximate MRF inference using bounded treewidth subgraphs
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Filter-Based mean-field inference for random fields with higher-order terms and product label-spaces
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part V
Contraction moves for geometric model fitting
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part VII
Tighter relaxations for higher-order models based on generalized roof duality
ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume Part III
Window annealing for pixel-labeling problems
Computer Vision and Image Understanding
Multi-view Scene Flow Estimation: A View Centered Variational Approach
International Journal of Computer Vision
Stereo reconstruction and contrast restoration in daytime fog
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part IV
Computer Vision and Image Understanding
Quadratic Transformation for Planar Mapping of Implicit Surfaces
Journal of Mathematical Imaging and Vision
A homography transform based higher-order MRF model for stereo matching
Pattern Recognition Letters
Hi-index | 0.14 |
Second-order priors on the smoothness of 3D surfaces are a better model of typical scenes than first-order priors. However, stereo reconstruction using global inference algorithms, such as graph cuts, has not been able to incorporate second-order priors because the triple cliques needed to express them yield intractable (nonsubmodular) optimization problems. This paper shows that inference with triple cliques can be effectively performed. Our optimization strategy is a development of recent extensions to \alpha--expansion, based on the “ QPBO” algorithm. The strategy is to repeatedly merge proposal depth maps using a novel extension of QPBO. Proposal depth maps can come from any source, for example, frontoparallel planes as in \alpha-expansion, or indeed any existing stereo algorithm, with arbitrary parameter settings.