The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mean Shift: A Robust Approach Toward Feature Space Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Hierarchical Estimation and Segmentation of Dense Motion Fields
International Journal of Computer Vision
Combining Intensity and Motion for Incremental Segmentation and Tracking Over Long Image Sequences
ECCV '92 Proceedings of the Second European Conference on Computer Vision
Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Skin and Bones: Multi-layer, Locally Affine, Optical Flow and Regularization with Transparency
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
High-quality video view interpolation using a layered representation
ACM SIGGRAPH 2004 Papers
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
Symmetric Stereo Matching for Occlusion Handling
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Towards Ultimate Motion Estimation: Combining Highest Accuracy with Real-Time Performance
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Consistent Segmentation for Optical Flow Estimation
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
Piecewise-Smooth Dense Optical Flow via Level Sets
International Journal of Computer Vision
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
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
Bilateral filtering-based optical flow estimation with occlusion detection
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Variational motion segmentation with level sets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
Improving sub-pixel correspondence through upsampling
Computer Vision and Image Understanding
Improving motion estimation using image-driven functions and hybrid scheme
PSIVT'11 Proceedings of the 5th Pacific Rim conference on Advances in Image and Video Technology - Volume Part I
Stochastic models for local optical flow estimation
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
Consistent Binocular Depth and Scene Flow with Chained Temporal Profiles
International Journal of Computer Vision
International Journal of Computer Vision
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Segmentation has gained in popularity in stereo matching. However, it is not trivial to incorporate it in optical flow estimation due to the possible non-rigid motion problem. In this paper, we describe a new optical flow scheme containing three phases. First, we partition the input images and integrate the segmentation information into a variational model where each of the segments is constrained by an affine motion. Then the errors brought in by segmentation are measured and stored in a confidence map. The final flow estimation is achieved through a global optimization phase that minimizes an energy function incorporating the confidence map. Extensive experiments show that the proposed method not only produces quantitatively accurate optical flow estimates but also preserves sharp motion boundaries, which makes the optical flow result usable in a number of computer vision applications, such as image/video segmentation and editing.