ML Anthology

Measuring the Quality of Figure/ground Segmentations

Michael Arens, C. Anderer
CVPRW 2010 pp. 52-59
doi:10.1109/CVPRW.2010.5543793 /cvprw/2010/arens2010cvprw-measuring/

Abstract

Figure/Ground segmentation is of great interest within the analysis of video streams. We propose a new, continuous evaluation measure for figure/ground segmentation algorithms which allows for assessing the quality of a segmentation. The evaluation approach is based on set similarities and logic-motivated considerations. Results obtained with the new measure are shown for several well-known algorithms. Compared to existing detection rate/false alarm considerations, the proposed measure reveals advantages and shortcommings of different algorithms much better and can therefore be used as a selection criterion.

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Cite

Text

Arens and Anderer. "Measuring the Quality of Figure/ground Segmentations." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010. doi:10.1109/CVPRW.2010.5543793

Markdown

[Arens and Anderer. "Measuring the Quality of Figure/ground Segmentations." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2010.](https://mlanthology.org/cvprw/2010/arens2010cvprw-measuring/) doi:10.1109/CVPRW.2010.5543793

BibTeX

@inproceedings{arens2010cvprw-measuring,
  title     = {{Measuring the Quality of Figure/ground Segmentations}},
  author    = {Arens, Michael and Anderer, C.},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2010},
  pages     = {52-59},
  doi       = {10.1109/CVPRW.2010.5543793},
  url       = {https://mlanthology.org/cvprw/2010/arens2010cvprw-measuring/}
}