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2006
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Selecting Distinctive 3D Shape Descriptors for Similarity Retrieval

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Selecting Distinctive 3D Shape Descriptors for Similarity Retrieval
Databases of 3D shapes have become widespread for a variety of applications, and a key research problem is searching these databases for similar shapes. This paper introduces a method for finding distinctive features of a shape that are useful for determining shape similarity. Although global shape descriptors have been developed to facilitate retrieval, they fail when local shape properties are the distinctive features of a class. Alternatively, local shape descriptors can be generated over the surface of shapes, but then storage and search of the descriptors becomes unnecessarily expensive, as perhaps only a few descriptors are sufficient to distinguish classes. The challenge is to select local descriptors from a query shape that are most distinctive for retrieval. Our approach is to define distinction as the retrieval performance of a local shape descriptor. During a training phase, we estimate descriptor likelihood using a multivariate Gaussian distribution of real-valued shape...
Philip Shilane, Thomas A. Funkhouser
Added 12 Jun 2010
Updated 12 Jun 2010
Type Conference
Year 2006
Where SMI
Authors Philip Shilane, Thomas A. Funkhouser
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