Objective functions for feature discrimination: theory
Proceedings of a workshop on Image understanding workshop
Proceedings of a workshop on Image understanding workshop
Digital Picture Processing
Information Theory and Reliable Communication
Information Theory and Reliable Communication
Deformable Template Recognition of Multiple Occluded Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
"Brownian Strings": Segmenting Images with Stochastically Deformable Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
On shape detection in noisy images with particular reference to ultrasonography
Statistics and Computing
A Bayesian Approach to in vivo Kidney Ultrasound Contour Detection Using Markov Random Fields
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part II
Deformable Contour Method: A Constrained Optimization Approach
International Journal of Computer Vision
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Describes a method of recognizing objects whose contours can be represented in smoothly varying polar coordinate form. Both low- and high-level information about the object (contour smoothness and edge sharpness at the low level and contour shape at the high level) are incorporated into a single energy function that defines a 1D, cyclic, Markov random field (1DCMRF). This 1DCMRF is based on a polar coordinate object representation whose center can be initialized at any location within the object. The recognition process is based on energy function minimization, which is implemented by simulated annealing.