ML Anthology

An Approach to Visualize Image Retrieval Results

Anke Schneidewind, Petra Neumann, Ingo Schmitt
CVPR 2004 pp. 148
doi:10.1109/CVPR.2004.297 /cvpr/2004/schneidewind2004cvpr-approach/

Abstract

Many current content-based image retrieval systems suffer from poor result presentation. A sophisticated visualization can be used to identify differences between human perception of similarity and system-determined similarity. Analyzing such discrepancies is a prerequisite for a system trimmed towards the user's comprehension of the underlying retrieval process. The aim of the visualization techniques presented in this paper is to provide a tool to analyze a mismatch between the user's perception and the system's calculation of similarity. We combine techniques of visual image retrieval and information visualization to acquire insight into the extracted feature data. In our project we implemented visualization techniques to present feature data on three different levels of abstraction. We discuss our experiences when working with a Data Table, a Parallel Coordinate Plot, and a Color Space Plot.

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Cite

Text

Schneidewind et al. "An Approach to Visualize Image Retrieval Results." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2004. doi:10.1109/CVPR.2004.297

Markdown

[Schneidewind et al. "An Approach to Visualize Image Retrieval Results." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2004.](https://mlanthology.org/cvpr/2004/schneidewind2004cvpr-approach/) doi:10.1109/CVPR.2004.297

BibTeX

@inproceedings{schneidewind2004cvpr-approach,
  title     = {{An Approach to Visualize Image Retrieval Results}},
  author    = {Schneidewind, Anke and Neumann, Petra and Schmitt, Ingo},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year      = {2004},
  pages     = {148},
  doi       = {10.1109/CVPR.2004.297},
  url       = {https://mlanthology.org/cvpr/2004/schneidewind2004cvpr-approach/}
}