Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Active shape models—their training and application
Computer Vision and Image Understanding
Machine vision
Deformable template models: a review
Signal Processing - Special issue on deformable models and techniques for image and signal processing
Equivalence of Hough curve detection to template matching
Communications of the ACM
State of the art in shape matching
Principles of visual information retrieval
The Geometry of Multiple Images: The Laws That Govern The Formation of Images of A Scene and Some of Their Applications
Computer and Robot Vision
Computer Vision: A Modern Approach
Computer Vision: A Modern Approach
Group Actions, Homeomorphisms, and Matching: A General Framework
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
A Multiphase Level Set Framework for Image Segmentation Using the Mumford and Shah Model
International Journal of Computer Vision
Using Prior Shapes in Geometric Active Contours in a Variational Framework
International Journal of Computer Vision
ECCV '98 Proceedings of the 5th European Conference on Computer Vision-Volume II - Volume II
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Region Matching with Missing Parts
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part III
Shape Similarity Measures, Properties and Constructions
VISUAL '00 Proceedings of the 4th International Conference on Advances in Visual Information Systems
Level Set Based Segmentation with Intensity and Curvature Priors
MMBIA '00 Proceedings of the IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
Multiple View Geometry in Computer Vision
Multiple View Geometry in Computer Vision
Vision: A Computational Investigation into the Human Representation and Processing of Visual Information
A Multiphase Dynamic Labeling Model for Variational Recognition-driven Image Segmentation
International Journal of Computer Vision
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Towards recognition-based variational segmentation using shape priors and dynamic labeling
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
IEEE Transactions on Image Processing
Shape-Based Mutual Segmentation
International Journal of Computer Vision
International Journal of Computer Vision
Geodesic Active Contours with Combined Shape and Appearance Priors
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Active Contours without Edges and with Simple Shape Priors
ACIVS '08 Proceedings of the 10th International Conference on Advanced Concepts for Intelligent Vision Systems
Extended Phase Field Higher-Order Active Contour Models for Networks
International Journal of Computer Vision
Segmentation using the edge strength function as a shape prior within a local deformation model
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part II
Image segmentation with one shape prior - A template-based formulation
Image and Vision Computing
Simultaneous monocular 2d segmentation, 3d pose recovery and 3d reconstruction
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part I
Computer Vision and Image Understanding
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Challenging object detection and segmentation tasks can be facilitated by the availability of a reference object. However, accounting for possible transformations between the different object views, as part of the segmentation process, remains difficult. Recent statistical methods address this problem by using comprehensive training data. Other techniques can only accommodate similarity transformations. We suggest a novel variational approach to prior-based segmentation, using a single reference object, that accounts for planar projective transformation. Generalizing the Chan-Vese level set framework, we introduce a novel shape-similarity measure and embed the projective homography between the prior shape and the image to segment within a region-based segmentation functional. The proposed algorithm detects the object of interest, extracts its boundaries, and concurrently carries out the registration to the prior shape. We demonstrate prior-based segmentation on a variety of images and verify the accuracy of the recovered transformation parameters.