Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Computation of component image velocity from local phase information
International Journal of Computer Vision
Performance of optical flow techniques
International Journal of Computer Vision
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Communications of the ACM
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint
Journal of Mathematical Imaging and Vision
Probabilistic Detection and Tracking of Motion Boundaries
International Journal of Computer Vision - Special issue on Genomic Signal Processing
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
A Multigrid Approach for Hierarchical Motion Estimation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
A Multigrid Approach for Hierarchical Motion Estimation
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Geodesic active regions and level set methods for motion estimation and tracking
Computer Vision and Image Understanding
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Discontinuity-preserving computation of variational optic flow in real-time
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Motion segmentation by multistage affine classification
IEEE Transactions on Image Processing
Coarse to over-fine optical flow estimation
Pattern Recognition
A Variational Technique for Time Consistent Tracking of Curves and Motion
Journal of Mathematical Imaging and Vision
Building Blocks for Computer Vision with Stochastic Partial Differential Equations
International Journal of Computer Vision
A Segmentation Based Variational Model for Accurate Optical Flow Estimation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Dynamic Texture Detection Based on Motion Analysis
International Journal of Computer Vision
Real time turbulent video perfecting by image stabilization and super-resolution
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Detecting regions of dynamic texture
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Illumination-robust variational optical flow using cross-correlation
Computer Vision and Image Understanding
Variational optic flow on the Sony PlayStation 3
Journal of Real-Time Image Processing
Optical flow or image subtraction in human detection from infrared camera on mobile robot
Robotics and Autonomous Systems
Group-Valued regularization framework for motion segmentation of dynamic non-rigid shapes
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Over-Parameterized optical flow using a stereoscopic constraint
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Discontinuity preserving registration of abdominal MR images with apparent sliding organ motion
MICCAI'11 Proceedings of the Third international conference on Abdominal Imaging: computational and Clinical Applications
A landmark-based primal-dual approach for discontinuity preserving registration
MICCAI'12 Proceedings of the 4th international conference on Abdominal Imaging: computational and clinical applications
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We propose a new algorithm for dense optical flow computation. Dense optical flow schemes are challenged by the presence of motion discontinuities. In state of the art optical flow methods, over-smoothing of flow discontinuities accounts for most of the error. A breakthrough in the performance of optical flow computation has recently been achieved by Brox et~al. Our algorithm embeds their functional within a two phase active contour segmentation framework. Piecewise-smooth flow fields are accommodated and flow boundaries are crisp. Experimental results show the superiority of our algorithm with respect to alternative techniques. We also study a special case of optical flow computation, in which the camera is static. In this case we utilize a known background image to separate the moving elements in the sequence from the static elements. Tests with challenging real world sequences demonstrate the performance gains made possible by incorporating the static camera assumption in our algorithm.