Algorithms for clustering data
Algorithms for clustering data
Bayesian Clustering for Unsupervised Estimation of Surface and Texture Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic extraction of deformable part models
International Journal of Computer Vision
The theory and practice of Bayesian image labeling
International Journal of Computer Vision
Learning internal representations by error propagation
Parallel distributed processing: explorations in the microstructure of cognition, vol. 1
On active contour models and balloons
CVGIP: Image Understanding
Natural object recognition
Boundary Finding with Parametrically Deformable Models
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature extraction from faces using deformable templates
International Journal of Computer Vision
A Bayesian Approach to Dynamic Contours Through Stochastic Sampling and Simulated Annealing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region-based strategies for active contour models
International Journal of Computer Vision
Parallel simulated annealing for shape detection
Computer Vision and Image Understanding
Object Matching Using Deformable Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Region Competition: Unifying Snakes, Region Growing, and Bayes/MDL for Multiband Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Visual Image Retrieval by Elastic Matching of User Sketches
IEEE Transactions on Pattern Analysis and Machine Intelligence
“Brownian strings”: segmenting images with stochastically deformable contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Deformable Template Recognition of Multiple Occluded Objects
IEEE Transactions on Pattern Analysis and Machine Intelligence
Cooperative Robust Estimation Using Layers of Support
IEEE Transactions on Pattern Analysis and Machine Intelligence
Segmentation using deformable models with affinity-based localization
CVRMed-MRCAS '97 Proceedings of the First Joint Conference on Computer Vision, Virtual Reality and Robotics in Medicine and Medial Robotics and Computer-Assisted Surgery
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Deformable Shape Detection and Description via Model-Based Region Grouping
Deformable Shape Detection and Description via Model-Based Region Grouping
Clump splitting via bottleneck detection and shape classification
Pattern Recognition
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A method for deformable shape-based image segmentation is described. Regions in an image are merged together and/or split apart, based on their agreement with an a priori distribution on the global deformation parameters for a shape template. Perceptually-motivated criteria are used to determine where and how to split regions, based on the local shape properties of the region group's bounding contour. In general, finding the globally optimal region partition for an image is an NP hard problem; therefore, two approximation strategies are employed: the highest confidence first algorithm and shape indexing trees. Experiments show that the speedup obtained through use of the approximation strategies is significant, while accuracy of segmentation remains high. Once trained, the system autonomously segments shapes from the background, while not merging them with adjacent objects or shadows.