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Shape Distinction for 3D Object Retrieval

Philip Shilane

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Paperback / softback
24 October 2008
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In recent years, there has been enormous growth in the number of 3D models and their availability to a wide segment of the population. Examples include the National Design Repository which stores 3D computer-aided design (CAD) models, the Protein Data Bank (PDB) that has atomic positions for protein molecules, and the Princeton Shape Benchmark with thousands of everyday objects represented as polygonal surface models. With the availability of free interactive tools for creating 3D models and graphics cards for home computers, we can expect 3D data to become ever more widely available.The first contribution of this research is an analysis technique to select the most important or distinctive regions of an object. Our approach identifies regions of a surface that have shape consistent with objects of the same type and different from objects of other types. The second contribution is a new methodology to analyze shape retrieval methods with a common data set of classified 3D models and software tools called the Princeton Shape Benchmark.This text should be especially useful to researchers in computer graphics, computer vision, CAD, and information retrieval.

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RRP: $109.21
$88.00
Ships in 3-5 business days
Hurry up! Current stock:

Shape Distinction for 3D Object Retrieval

RRP: $109.21
$88.00

Description

In recent years, there has been enormous growth in the number of 3D models and their availability to a wide segment of the population. Examples include the National Design Repository which stores 3D computer-aided design (CAD) models, the Protein Data Bank (PDB) that has atomic positions for protein molecules, and the Princeton Shape Benchmark with thousands of everyday objects represented as polygonal surface models. With the availability of free interactive tools for creating 3D models and graphics cards for home computers, we can expect 3D data to become ever more widely available.The first contribution of this research is an analysis technique to select the most important or distinctive regions of an object. Our approach identifies regions of a surface that have shape consistent with objects of the same type and different from objects of other types. The second contribution is a new methodology to analyze shape retrieval methods with a common data set of classified 3D models and software tools called the Princeton Shape Benchmark.This text should be especially useful to researchers in computer graphics, computer vision, CAD, and information retrieval.

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