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» Shapes as empirical distributions
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CVPR
2000
IEEE
15 years 1 months ago
Statistical Shape Influence in Geodesic Active Contours
A novel method of incorporating shape information into the image segmentation process is presented. We introduce a representation for deformable shapes and define a probability di...
Michael E. Leventon, W. Eric L. Grimson, Olivier D...
BMVC
1998
14 years 11 months ago
Building Shape Models from Image Sequences using Piecewise Linear Approximation
A method of extracting, classifying and modelling non-rigid shapes from an image sequence is presented. Shapes are approximated by polygons where the number of sides is related to...
Derek R. Magee, Roger D. Boyle
ICANN
2010
Springer
14 years 8 months ago
Dynamic Shape Learning and Forgetting
In this paper, we present a system capable of dynamically learning shapes in a way that also allows for the dynamic deletion of shapes already learned. It uses a self-balancing Bin...
Nikolaos Tsapanos, Anastasios Tefas, Ioannis Pitas
JMIV
2010
98views more  JMIV 2010»
14 years 8 months ago
Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions
Shape estimation and object reconstruction are common problems in image analysis. Mathematically, viewing objects in the image plane as random sets reduces the problem of shape es...
Hanna K. Jankowski, Larissa I. Stanberry
CVPR
2009
IEEE
16 years 4 months ago
An Empirical Bayes Approach to Contextual Region Classification
This paper presents a nonparametric approach to labeling of local image regions that is inspired by recent developments in information-theoretic denoising. The chief novelty of ...
Svetlana Lazebnik (UNC Chapel Hill), Maxim Raginsk...