A comparison of text and shape matching for retrieval of online 3D models

Patrick Min, Michael Kazhdan, Thomas Funkhouser

Research output: Chapter in Book/Report/Conference proceedingChapter

50 Scopus citations

Abstract

Because of recent advances in graphics hard- and software, both the production and use of 3D models are increasing at a rapid pace. As a result, a large number of 3D models have become available on the web, and new research is being done on 3D model retrieval methods. Query and retrieval can be done solely based on associated text, as in image retrieval, for example (e.g. Google Image Search [1] and [2, 3]). Other research focuses on shape-based retrieval, based on methods that measure shape similarity between 3D models (e.g., [4]). The goal of our work is to take current text- and shape-based matching methods, see which ones perform best, and compare those. We compared four text matching methods and four shape matching methods, by running classification tests using a large database of 3D models downloaded from the web [5]. In addition, we investigated several methods to combine the results of text and shape matching. We found that shape matching outperforms text matching in all our experiments. The main reason is that publishers of online 3D models simply do not provide enough descriptive text of sufficient quality: 3D models generally appear in lists on web pages, annotated only with cryptic filenames or thumbnail images. Combining the results of text and shape matching further improved performance. The results of this paper provide added incentive to continue research in shape-based retrieval methods for 3D models, as well as retrieval based on other attributes.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsRachel Heery, Liz Lyon
PublisherSpringer Verlag
Pages209-220
Number of pages12
ISBN (Print)3540230130, 9783540230137
DOIs
StatePublished - Jan 1 2004

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3232
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Min, P., Kazhdan, M., & Funkhouser, T. (2004). A comparison of text and shape matching for retrieval of online 3D models. In R. Heery, & L. Lyon (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 209-220). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3232). Springer Verlag. https://doi.org/10.1007/978-3-540-30230-8_20