Summary: Discriminating deformable shape classes
S. Ruiz-Correa

, L. G. Shapiro

, M. Meila
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and G. Berson
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Department of Electrical Engineering¤
Department of Statistics¢
Division of Medical Genetics, School of Medicine
University of Washington, Seattle, WA 98105
Abstract
We present and empirically test a novel approach for categorizing 3-D free form object
shapes represented by range data. In contrast to traditional surface-signature based systems
that use alignment to match specific objects, we adapted the newly introduced symbolic-
signature representation to classify deformable shapes [12]. Our approach constructs an
abstract description of shape classes using an ensemble of classifiers that learn object class

Source: Anderson, Richard - Department of Computer Science and Engineering, University of Washington at Seattle

Collections: Computer Technologies and Information Sciences