Object Detection and Localization by Dynamic Template Warping
International Journal of Computer Vision
Comparison and Classification of Documents Based on Layout Similarity
Information Retrieval
International Journal of Computer Vision - Special Issue on Content-Based Image Retrieval
Recognition of object categories using affine kernels
Proceedings of the international conference on Multimedia information retrieval
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In content-based access of image databases, there is a need for a shape formalism that allows a precise description and recognition of a wider class of shape variations that evoke the same overall perceptual similarity in appearance. Such a description not only allows images of a database to be organized into shape categories for efficient indexing, but also makes a wider class of shape-similarity queries possible. This paper presents a region topology-based model called the constrained affine shape model, that captures the spatial layout similarity between members of a class by a set of constrained affine deformations from a prototypical member. The shape model is proposed for use in organizing images of a database into shape categories represented by prototypical members and the associated shape constraints. An efficient matching algorithm is presented for use in shape categorization and querying. Effect of global pose changes on the constraints of the shape model are analyzed to make shape matching robust to global pose changes. An application of the model for document retrieval based on document shape genres is presented. Finally, the effectiveness of the shape model in content-based access of such databases is evaluated.