Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Machine Vision and Applications
On active contour models and balloons
CVGIP: Image Understanding
A level set approach for computing solutions to incompressible two-phase flow
Journal of Computational Physics
Shape Modeling with Front Propagation: A Level Set Approach
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Active Testing Model for Tracking Roads in Satellite Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic Finding of Main Roads in Aerial Images by Using Geometric-Stochastic Models and Estimation
IEEE Transactions on Pattern Analysis and Machine Intelligence
New Prospects in Line Detection by Dynamic Programming
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Geometric shock-capturing eno schemes for subpixel interpolation, computation and curve evolution
Graphical Models and Image Processing
International Journal of Computer Vision
Planar shape enhancement and exaggeration
Graphical Models and Image Processing
The fast construction of extension velocities in level set methods
Journal of Computational Physics
SIAM Journal on Scientific Computing
SIAM Review
Automatic extraction of roads from aerial images based on scale space and snakes
Machine Vision and Applications
Globally Optimal Regions and Boundaries as Minimum Ratio Weight Cycles
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Flux Maximizing Geometric Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Regularized Laplacian Zero Crossings as Optimal Edge Integrators
International Journal of Computer Vision
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
On the Incorporation of shape priors into geometric active contours
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
VLSM '01 Proceedings of the IEEE Workshop on Variational and Level Set Methods (VLSM'01)
Gradient flows and geometric active contour models
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
A Gibbs Point Process for Road Extraction from Remotely Sensed Images
International Journal of Computer Vision
IEEE Transactions on Image Processing
International Journal of Computer Vision
Higher-Order Active Contour Energies for Gap Closure
Journal of Mathematical Imaging and Vision
Fourier-based geometric shape prior for snakes
Pattern Recognition Letters
Shape-Based Mutual Segmentation
International Journal of Computer Vision
Shape feature control in structural topology optimization
Computer-Aided Design
Prediction and change detection in sequential data for interactive applications
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Stabilization of parametric active contours using a tangential redistribution term
IEEE Transactions on Image Processing
Efficient implementation for spherical flux computation and its application to vascular segmentation
IEEE Transactions on Image Processing
A Deformable Surface Model for Vascular Segmentation
MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
Extended Phase Field Higher-Order Active Contour Models for Networks
International Journal of Computer Vision
Detection and completion of filaments: a vector field and PDE approach
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
A new phase field model of a 'gas of circles' for tree crown extraction from aerial images
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Simultaneous object classification and segmentation with high-order multiple shape models
IEEE Transactions on Image Processing
A family of quadratic snakes for road extraction
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
A Markov random field model for extracting near-circular shapes
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Continuous force field analysis for generalized gradient vector flow field
Pattern Recognition
Adaptive smoothness based robust active contours
Image and Vision Computing
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Robust active contour segmentation with an efficient global optimizer
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Road Detection and Tracking from Aerial Desert Imagery
Journal of Intelligent and Robotic Systems
Archaeological trace extraction by a local directional active contour approach
Pattern Recognition
Efficient monte carlo sampler for detecting parametric objects in large scenes
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part III
Journal of Visual Communication and Image Representation
Detecting parametric objects in large scenes by Monte Carlo sampling
International Journal of Computer Vision
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We introduce a new class of active contour models that hold great promise for region and shape modelling, and we apply a special case of these models to the extraction of road networks from satellite and aerial imagery. The new models are arbitrary polynomial functionals on the space of boundaries, and thus greatly generalize the linear functionals used in classical contour energies. While classical energies are expressed as single integrals over the contour, the new energies incorporate multiple integrals, and thus describe long-range interactions between different sets of contour points. As prior terms, they describe families of contours that share complex geometric properties, without making reference to any particular shape, and they require no pose estimation. As likelihood terms, they can describe multi-point interactions between the contour and the data. To optimize the energies, we use a level set approach. The forces derived from the new energies are non-local however, thus necessitating an extension of standard level set methods. Networks are a shape family of great importance in a number of applications, including remote sensing imagery. To model them, we make a particular choice of prior quadratic energy that describes reticulated structures, and augment it with a likelihood term that couples the data at pairs of contour points to their joint geometry. Promising experimental results are shown on real images.