Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Surface modeling with oriented particle systems
SIGGRAPH '92 Proceedings of the 19th annual conference on Computer graphics and interactive techniques
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
A hierarchical Markov modeling approach for the segmentation and tracking of deformable shapes
Graphical Models and Image Processing
Finding Shortest Paths on Surfaces Using Level Sets Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 3
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
Snake Pedals: Geometric Models with Physics-Based Control
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Tracking Meteorological Structures through Curves Matching Using Geodesic Paths
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
2D motion description and contextual motion analysis: issues and new models
SCVMA'04 Proceedings of the First international conference on Spatial Coherence for Visual Motion Analysis
Journal of Visual Communication and Image Representation
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Tracking and characterizing convective clouds from meteorological satellite images enable to evaluate the potential occurring of strong precipitation. We propose an original two-step tracking method based on the Level Set approach which can efficiently cope with frequent splitting or merging phases undergone by such highly deformable structures. The first step exploits a 2D motion field, and acts as a prediction step. The second step can produce, by comparinglo cal and global photometric information, appropriate expansion or contraction forces on the evolving contours to accurately locate the cloud cells of interest. The characterization of the tracked clouds relies on both 2D local motion divergence information and temporal variations of temperature. It is formulated as a contextual statistical labeling problem involving three classes "growing activity", "declining activity" and "inactivity".