The Princeton Shape Benchmark

Philip Shilane, Patrick Min, Michael Kazhdan, Thomas Funkhouser

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1315 Scopus citations


In recent years, many shape representations and geometric algorithms have been proposed for matching 3D shapes. Usually, each algorithm is tested on a different (small) database of 3D models, and thus no direct comparison is available for competing methods. In this paper, we describe the Princeton Shape Benchmark (PSB), a publicly available database of polygonal models collected from the World Wide Web and a suite of tools for comparing shape matching and classification algorithms. One feature of the benchmark is that it provides multiple semantic labels for each 3D model. For instance, it includes one classification of the 3D models based on function, another that considers function and form, and others based on how the object was constructed (e.g., man-made versus natural objects). We find that experiments with these classifications can expose different properties of shape-based retrieval algorithms. For example, out of 12 shape descriptors tested, Extended Gaussian Images [13] performed best for distinguishing man-made from natural objects, while they performed among the worst for distinguishing specific object types. Based on experiments with several different shape descriptors, we conclude that no single descriptor is best for all classifications, and thus the main contribution of this paper is to provide a framework to determine the conditions under which each descriptor performs best.

Original languageEnglish (US)
Title of host publicationProceedings - Shape Modeling International SMI 2004
EditorsF. Giannini, A. Pasko
Number of pages12
StatePublished - 2004
EventProceedings - Shape Modeling International SMI 2004 - Genova, Italy
Duration: Jun 7 2004Jun 9 2004

Publication series

NameProceedings - Shape Modeling International SMI 2004


OtherProceedings - Shape Modeling International SMI 2004

All Science Journal Classification (ASJC) codes

  • General Engineering


  • Benchmarks
  • Geometric matching
  • Shape database
  • Shape retrieval


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