ML Anthology

Efficient Query Refinement for Image Retrieval

Chahab Nastar, Matthias Mitschke, Christophe Meilhac
CVPR 1998 pp. 547-552
doi:10.1109/CVPR.1998.698659 /cvpr/1998/nastar1998cvpr-efficient/

Abstract

Although powerful image representations have been proposed for content-based image retrieval, most of the current systems are "rigid", i.e. they retrieve a fixed set of images as response to a given query and an image feature. In this paper, our goal is to introduce tools for making image retrieval systems more flexible. More precisely, we use multiple image features, and present in details a new relevance feedback technique that integrates the positive and negative examples provided by the user. Experimental results on various large databases show that the proposed technique is more performant than the standard relevance feedback approach.

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Cite

Text

Nastar et al. "Efficient Query Refinement for Image Retrieval." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998. doi:10.1109/CVPR.1998.698659

Markdown

[Nastar et al. "Efficient Query Refinement for Image Retrieval." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1998.](https://mlanthology.org/cvpr/1998/nastar1998cvpr-efficient/) doi:10.1109/CVPR.1998.698659

BibTeX

@inproceedings{nastar1998cvpr-efficient,
  title     = {{Efficient Query Refinement for Image Retrieval}},
  author    = {Nastar, Chahab and Mitschke, Matthias and Meilhac, Christophe},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {1998},
  pages     = {547-552},
  doi       = {10.1109/CVPR.1998.698659},
  url       = {https://mlanthology.org/cvpr/1998/nastar1998cvpr-efficient/}
}