Solved and unsolved problems in number theory
Solved and unsolved problems in number theory
Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
FORMS: a flexible object recognition and modeling system
International Journal of Computer Vision
Stochastic Jump-Diffusion Process for Computing Medial Axes in Markov Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: modeling, learning, sampling and computing, Part I
Stochastic Complexity in Statistical Inquiry Theory
Stochastic Complexity in Statistical Inquiry Theory
Symmetry-Based Indexing of Image Databases
CBAIVL '98 Proceedings of the IEEE Workshop on Content - Based Access of Image and Video Libraries
Fast Realistic Human Body Deformations for Animation and VR Applications
CGI '96 Proceedings of the 1996 Conference on Computer Graphics International
A shock grammar for recognition
CVPR '96 Proceedings of the 1996 Conference on Computer Vision and Pattern Recognition (CVPR '96)
On the Intrinsic Reconstruction of Shape from Its Symmetries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Untangling the Blum Medial Axis Transform
International Journal of Computer Vision - Special Issue on Research at the University of North Carolina Medical Image Display Analysis Group (MIDAG)
Analysis of Planar Shapes Using Geodesic Paths on Shape Spaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 4 - Volume 04
Determining the Geometry of Boundaries of Objects from Medial Data
International Journal of Computer Vision
Image Parsing: Unifying Segmentation, Detection, and Recognition
International Journal of Computer Vision
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We propose efficiency of representation as a criterion forevaluating shape models, then apply this criterion to compare theboundary curve representation with the medial axis. We estimate the⋮-entropy of two compact classes of curves. We then constructtwo adaptive encodings for non-compact classes of shapes, one usingthe boundary curve and the other using the medial axis, anddetermine precise conditions for when the medial axis is moreefficient. Finally, we apply our results to databases of naturallyoccurring shapes, determining whether the boundary or medial axisis more efficient. Along the way we construct explicit near-optimalboundary-based approximations for compact classes of shapes,construct an explicit compression scheme for non-compact classes ofshapes based on the medial axis, and derive some new results aboutthe medial axis.