Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow
IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of discontinuous optical flow by domain decomposition and shape optimization
International Journal of Computer Vision
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
SIAM Journal on Numerical Analysis
Direct incremental model-based image motion segmentation for video analysis
Signal Processing - Video segmentation for content-based processing manipulation
Image Sequence Analysis via Partial Differential Equations
Journal of Mathematical Imaging and Vision
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Nonlinear Shape Statistics in Mumford-Shah Based Segmentation
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Dense estimation and object-based segmentation of the optical flow with robust techniques
IEEE Transactions on Image Processing
Statistical deformable model-based segmentation of image motion
IEEE Transactions on Image Processing
Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Segmentation of a Vector Field: Dominant Parameter and Shape Optimization
Journal of Mathematical Imaging and Vision
International Journal of Computer Vision
Journal of Mathematical Imaging and Vision
A Segmentation Based Variational Model for Accurate Optical Flow Estimation
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
A Geometric Framework and a New Criterion in Optical Flow Modeling
Journal of Mathematical Imaging and Vision
Crowd Flow Segmentation Using a Novel Region Growing Scheme
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Bayesian approaches to motion-based image and video segmentation
IWCM'04 Proceedings of the 1st international conference on Complex motion
A multiphase level set framework for motion segmentation
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
Joint non-rigid motion estimation and segmentation
IWCIA'04 Proceedings of the 10th international conference on Combinatorial Image Analysis
Morphons: paint on priors and elastic canvas for segmentation and registration
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
A shape derivative based approach for crowd flow segmentation
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part I
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We present a variational method for the segmentation of piecewise affine flow fields. Compared to other approaches to motion segmentation, we minimize a single energy functional both with respect to the affine motion models in the separate regions and with respect to the shape of the separating contour. In the manner of region competition, the evolution of the segmenting contour is driven by a force which aims at maximizing a homogeneity measure with respect to the estimated motion in the adjoining regions.We compare segmentations obtained for the models of piecewise affine motion, piecewise constant motion, and piecewise constant intensity. For objects which cannot be discriminated from the background by their appearance, the desired motion segmentation is obtained, although the corresponding segmentation based on image intensities fails. The region-based formulation facilitates convergence of the contour from its initialization over fairly large distances, and the estimated discontinuous flow field is progressively improved during the gradient descent minimization. By including in the variational method a statistical shape prior, the contour evolution is restricted to a subspace of familiar shapes, such that a robust estimation of irregularly moving shapes becomes feasible.