Feature-based similarity search in 3D object databases

  • Authors:

  • Benjamin Bustos;Daniel A. Keim;Dietmar Saupe;Tobias Schreck;Dejan V. Vranić

  • Affiliations:

  • University of Konstanz, Konstanz, Germany;University of Konstanz, Konstanz, Germany;University of Konstanz, Konstanz, Germany;University of Konstanz, Konstanz, Germany;University of Konstanz, Konstanz, Germany

  • Venue:
  • ACM Computing Surveys (CSUR)
  • Year:
  • 2005

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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.