International Journal of Computer Vision
Game-Theoretic Integration for Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Level-Set Approach to 3D Reconstruction from Range Data
International Journal of Computer Vision
Snake Pedals: Compact and Versatile Geometric Models with Physics-Based Control
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - special issue on learning and vision at the center for biological and computational learning, Massachusetts Institute of Technology
Deformable Shape Detection and Description via Model-Based Region Grouping
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the sixth ACM symposium on Solid modeling and applications
Advanced algorithmic approaches to medical image segmentation
A Variational Approach for the Segmentation of the Left Ventricle in Cardiac Image Analysis
International Journal of Computer Vision
Direct surface extraction from 3D freehand ultrasound images
Proceedings of the conference on Visualization '02
Flux Maximizing Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
New Algorithms for Controlling Active Contours Shape and Topology
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part II
Journal of Computational Physics
A Geometric Approach to Segmentation and Analysis of 3D Medical Images
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
MMBIA '96 Proceedings of the 1996 Workshop on Mathematical Methods in Biomedical Image Analysis (MMBIA '96)
Gradient Vector Flow Fast Geometric Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
A review of vessel extraction techniques and algorithms
ACM Computing Surveys (CSUR)
Surface Reconstruction of Noisy and Defective Data Sets
VIS '04 Proceedings of the conference on Visualization '04
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Proceedings of the 2005 ACM symposium on Applied computing
G-wire: A livewire segmentation algorithm based on a generalized graph formulation
Pattern Recognition Letters
Affine-Invariant Geometric Shape Priors for Region-Based Active Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Active contours using a constraint-based implicit representation
SIGGRAPH '05 ACM SIGGRAPH 2005 Courses
International Journal of Computer Vision
Topological control of level set method depending on topology constraints
Pattern Recognition Letters
Nonlinear Dynamical Shape Priors for Level Set Segmentation
Journal of Scientific Computing
Force field analysis snake: an improved parametric active contour model
Pattern Recognition Letters
Information Sciences: an International Journal
A graphical model framework for coupling MRFs and deformable models
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Water flow based complex feature extraction
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
A geometric contour framework with vector field support
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
Active strokes: coherent line stylization for animated 3D models
NPAR '12 Proceedings of the Symposium on Non-Photorealistic Animation and Rendering
Flexible and topologically localized segmentation
EUROVIS'07 Proceedings of the 9th Joint Eurographics / IEEE VGTC conference on Visualization
Extracting boundary surface of arbitrary topology from volumetric datasets
VG'01 Proceedings of the 2001 Eurographics conference on Volume Graphics
Pattern Recognition and Image Analysis
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The paper presents a typologically adaptable snakes model for image segmentation and object representation. The model is embedded in the framework of domain subdivision using simplicial decomposition. This framework extends the geometric and topological adaptability of snakes while retaining all of the features of traditional snakes, such as user interaction, and overcoming many of the limitations of traditional snakes. By superposing a simplicial grid over the image domain and using this grid to iteratively reparameterize the deforming snakes model, the model is able to flow into complex shapes, even shapes with significant protrusions or branches, and to dynamically change topology as necessitated by the data. Snakes can be created and can split into multiple parts or seamlessly merge into other snakes. The model can also be easily converted to and from the traditional parametric snakes model representation. We apply a 2D model to various synthetic and real images in order to segment objects with complicated shapes and topologies.