Stan Sclaroff,
Deformable Prototypes for Encoding Shape Categories in
Image Databases,
Pattern Recognition,
30, 4, pp. 627-642, April 1997.
Stan Sclaroff,
Deformable Prototypes for Encoding Shape Categories in
Image Databases,
Pattern Recognition,
30, 4, pp. 627-642, April 1997.We describe a method for shape-based image database search that uses deformable prototypes to represent categories. Rather than directly comparing a candidate shape with all shape entries in the database, shapes are compared in terms of the types of nonrigid deformations (differences) that relate them to a small subset of representative prototypes. To solve the shape correspondence and alignment problem, we employ the technique of modal matching, an information-preserving shape decomposition for matching, describing, and comparing shapes despite sensor variations and nonrigid deformations. In modal matching, shape is decomposed into an ordered basis of orthogonal principal components. We demonstrate the utility of this approach for shape comparison in 2-D image databases.