Diffusion Snakes: Introducing Statistical Shape Knowledge into the Mumford-Shah Functional
International Journal of Computer Vision
Shape Priors for Level Set Representations
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Topologically adaptable snakes
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
B-spline active contour with handling of topology changes for fast video segmentation
EURASIP Journal on Applied Signal Processing
Fourier-based geometric shape prior for snakes
Pattern Recognition Letters
A new version of Flusser moment set for pattern feature extraction
WSEAS Transactions on Information Science and Applications
Multi-Reference Shape Priors for Active Contours
International Journal of Computer Vision
New Possibilities with Sobolev Active Contours
International Journal of Computer Vision
Simultaneous brain structures segmentation combining shape and pose forces
MBIA'11 Proceedings of the First international conference on Multimodal brain image analysis
Affine-invariant curvature estimators for implicit surfaces
Computer Aided Geometric Design
Fast finsler active contours and shape prior descriptor
CIARP'11 Proceedings of the 16th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Segmentation of prostate using interactive finsler active contours and shape prior
ICISP'12 Proceedings of the 5th international conference on Image and Signal Processing
Active shape model based on sparse representation
CCBR'12 Proceedings of the 7th Chinese conference on Biometric Recognition
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We present a new way of constraining the evolution of a region-based active contour with respect to a reference shape. Minimizing a shape prior, defined as a distance between shape descriptors based on the Legendre moments of the characteristic function, leads to a geometric flow that can be used with benefits in a two-class segmentation application. The shape model includes intrinsic invariance with regard to pose and affine deformations.