Learning to track the visual motion of contours
Artificial Intelligence - Special volume on computer vision
Physics-Based Deformable Models: Applications to Computer Vision, Graphics, and Medical Imaging
Physics-Based Deformable Models: Applications to Computer Vision, Graphics, and Medical Imaging
Elastically Adaptive Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Bounds on the Optimal Elasticity Parameters for a Snake
ICIAP '95 Proceedings of the 8th International Conference on Image Analysis and Processing
Geometric Level Set Methods in Imaging,Vision,and Graphics
Geometric Level Set Methods in Imaging,Vision,and Graphics
Frequency Domain Formulation of Active Parametric Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Stability and convergence of the level set method in computer vision
Pattern Recognition Letters
Boundary vector field for parametric active contours
Pattern Recognition
Fundamentals of Stop and Go active models
Image and Vision Computing
Force field analysis snake: an improved parametric active contour model
Pattern Recognition Letters
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Interpolation and the discrete Papoulis-Gerchberg algorithm
IEEE Transactions on Signal Processing
Snakes, shapes, and gradient vector flow
IEEE Transactions on Image Processing
Dynamic directional gradient vector flow for snakes
IEEE Transactions on Image Processing
Multigrid Geometric Active Contour Models
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Continuous force field analysis for generalized gradient vector flow field
Pattern Recognition
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Active contours are very useful tools in image segmentation and object tracking in video sequences. The practical implementations are built with an iterative algorithm based on a second order system defined in the spatial domain, where the elasticity and rigidity are the static parameters for its characterization and mass and damping are the dynamic parameters. In the process, the contour is influenced by external and internal forces varying its shape adaptively. The number of iterations required by the contour to delineate the objects is determined by these forces, by its initialization and by the coefficients of the second order system. This paper analyzes the convergence of active contours using the frequency based formulation and shows that the convergence depends on the dynamic parameters of the second order system and the distance between nodes of the contour attracted by the external forces.