article

Feature-based similarity search in 3D object databases

Authors:

Benjamin Bustos,

Daniel A. Keim,

Tobias Schreck,

Dejan V. VranićAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 37, Issue 4

Pages 345 - 387

https://doi.org/10.1145/1118890.1118893

Published: 01 December 2005 Publication History

Abstract

The development of effective content-based multimedia search systems is an important research issue due to the growing amount of digital audio-visual information. In the case of images and video, the growth of digital data has been observed since the introduction of 2D capture devices. A similar development is expected for 3D data as acquisition and dissemination technology of 3D models is constantly improving. 3D objects are becoming an important type of multimedia data with many promising application possibilities. Defining the aspects that constitute the similarity among 3D objects and designing algorithms that implement such similarity definitions is a difficult problem. Over the last few years, a strong interest in methods for 3D similarity search has arisen, and a growing number of competing algorithms for content-based retrieval of 3D objects have been proposed. We survey feature-based methods for 3D retrieval, and we propose a taxonomy for these methods. We also present experimental results, comparing the effectiveness of some of the surveyed methods.

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Index Terms

Feature-based similarity search in 3D object databases
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Image and video acquisition
        3D imaging
  2. Computer graphics
    1. Animation
    2. Shape modeling
      1. Parametric curve and surface models
      2. Volumetric models
2. Information systems
  1. Information retrieval

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cover image ACM Computing Surveys

ACM Computing Surveys Volume 37, Issue 4

December 2005

111 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/1118890

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Copyright © 2005 ACM.

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Published: 01 December 2005

Published in CSUR Volume 37, Issue 4

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