Shape-Guided Split and Merge of Image Regions
IWVF-4 Proceedings of the 4th International Workshop on Visual Form
Automatic Deformable Shape Segmentation for Image Database Search Applications
VISUAL '99 Proceedings of the Third International Conference on Visual Information and Information Systems
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Abstract A method for deformable shape detection and recognition is described. Deformable shape templates are used to partition the image into a globally consistent interpretation, determined in part by the minimum description length principle. Statistical shape models enforce the prior probabilities on global, parametric deformations for each object class. Once trained, the system autonomously segments deformed shapes from the background, while not merging them with adjacent objects or shadows. The formulation can be used to group image regions based on any image homogeneity predicate; e.g., texture, color, or motion. The recovered shape models can be used directly in object recognition. Experiments with color imagery are reported. Note: This TR supercedes BUCS-TR-1997-019