The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Fast Approximate Energy Minimization via Graph Cuts
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Stereo with Multiple Windowing
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Adaptive Support-Weight Approach for Correspondence Search
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient Belief Propagation for Early Vision
International Journal of Computer Vision
Convergent Tree-Reweighted Message Passing for Energy Minimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient MRF deformation model for non-rigid image matching
Computer Vision and Image Understanding
Two Applications of Graph-Cuts to Image Processing
DICTA '08 Proceedings of the 2008 Digital Image Computing: Techniques and Applications
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Fusion Moves for Markov Random Field Optimization
IEEE Transactions on Pattern Analysis and Machine Intelligence
A high-quality video denoising algorithm based on reliable motion estimation
ECCV'10 Proceedings of the 11th European conference on computer vision conference on Computer vision: Part III
Robust Stereo Matching Using Adaptive Normalized Cross-Correlation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Bayesian approach to adaptive video super resolution
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Fast cost-volume filtering for visual correspondence and beyond
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Hardware-Efficient Belief Propagation
IEEE Transactions on Circuits and Systems for Video Technology
Motion Detail Preserving Optical Flow Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
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We propose a scheme for comparing local neighborhoods (window) of image points, to estimate optical flow using discrete optimization. The proposed approach is based on using large correlation windows with adaptive support-weights. We present three new types of weighting constraints derived from image gradient, color statistics and occlusion information. The first type provides gradient structure constraints that favor flow consistency across strong image gradients. The second type imposes perceptual color constraints that reinforce relationship among pixels in a window according to their color statistics. The third type yields occlusion constraints that reject pixels that are seen in one window but not seen in the other. All these constraints contribute to suppress the effect of cluttered background, which is unavoidably included in the large correlation windows. Experimental results demonstrate that each of the proposed constraints appreciably elevates the quality of estimations, and that they jointly yield results that compare favorably to current techniques, especially on object boundaries.