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Cited by 425

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Indexing via color histograms

Swain, M.J., Ballard, D.H.·2002·[1990] Proceedings Third International Conference on Computer Vision
DOI 10.1109/iccv.1990.139558
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Abstract

This paper shows color histograms to be stable object representations over change in view, and demonstrates that they can differentiate among a large number of objects. The authors introduce a technique called histogram intersection for efficiently matching model and image histograms. Color can also be used to search for the location of an object. An algorithm called histogram backprojection performs this task efficiently in crowded scenes.>

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Metadata

Authors
Swain, M. J., & Ballard, D. H.
Venue
[1990] Proceedings Third International Conference on Computer Vision
Publisher
IEEE Comput. Soc. Press
Published
2002-12-04
Pages
390-393
DOI
10.1109/iccv.1990.139558
OpenAlex
W2105994593
Cited by
425
References
11
Type
paratext
Language
en
Open access
closed

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CoChat. (2026). Citation check: Indexing via color histograms. https://app.cochat.ai/papers/10.1109/iccv.1990.139558
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Swain, M. J., & Ballard, D. H. (2002). Indexing via color histograms. [1990] Proceedings Third International Conference on Computer Vision. https://doi.org/10.1109/iccv.1990.139558

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.