Form representions and means for landmarks: a survey and comparative study
Computer Vision and Image Understanding
Shape Representation and Classification Using the Poisson Equation
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Towards segmentation based on a shape prior manifold
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Dynamical statistical shape priors for level set based sequence segmentation
VLSM'05 Proceedings of the Third international conference on Variational, Geometric, and Level Set Methods in Computer Vision
A hybrid eulerian-lagrangian approach for thickness, correspondence, and gridding of annular tissues
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
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We present a novel representation of shape for closedplanar contours explicitly designed to possess a linearstructure. This greatly simplifies linear operations suchas averaging, principal component analysis or differentiation in the space of shapes. The representation reliesupon embedding the contour on a subset of the space ofharmonic functions of which the original contour is thezero level set.