Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Computation of discontinuous optical flow by domain decomposition and shape optimization
International Journal of Computer Vision
Computing minimal surfaces via level set curvature flow
Journal of Computational Physics
Region-based strategies for active contour models
International Journal of Computer Vision
Multi-stage segmentation of optical flow field
Signal Processing
International Journal of Computer Vision
The fast construction of extension velocities in level set methods
Journal of Computational Physics
Computing optical flow via variational techniques
SIAM Journal on Applied Mathematics
Shapes and geometries: analysis, differential calculus, and optimization
Shapes and geometries: analysis, differential calculus, and optimization
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint
Journal of Mathematical Imaging and Vision
International Journal of Computer Vision
Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Refinement of Optical Flow Estimation and Detection of Motion Edges
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Displacement Following of Hidden Objects in a Video Sequence
International Journal of Computer Vision
Adaptive Grid Refinement Procedures for Efficient Optical Flow Computation
International Journal of Computer Vision
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
B-spline snakes: a flexible tool for parametric contour detection
IEEE Transactions on Image Processing
Segmentation of Vectorial Image Features Using Shape Gradients and Information Measures
Journal of Mathematical Imaging and Vision
Journal of Mathematical Imaging and Vision
From Inpainting to Active Contours
International Journal of Computer 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
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
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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Vector field segmentation methods usually belong to either of three classes: methods which segment regions homogeneous in direction and/or norm, methods which detect discontinuities in the vector field, and region growing or classification methods. The first two classes of method do not allow segmentation of complex vector fields and control of the type of fields to be segmented, respectively. The third class does not directly allow a smooth representation of the segmentation boundaries. In the particular case where the vector field actually represents an optical flow, a fourth class of methods acts as a detector of main motion. The proposed method combines a vector field model and a theoretically founded minimization approach. Compared to existing methods following the same philosophy, it relies on an intuitive, geometric way to define the model while preserving a general point of view adapted to the segmentation of potentially complex vector fields with the condition that they can be described by a finite number of parameters. The energy to be minimized is deduced from the choice of a specific class of field lines, e.g. straight lines or circles, described by the general form of their parametric equations. In that sense, the proposed method is a principled approach for segmenting parametric vector fields. The minimization problem was rewritten into a shape optimization and implemented by spline-based active contours. The algorithm was applied to the segmentation of precomputed optical flow fields given by an external, independent algorithm.