SEISM – Supervised Evaluation of Image Segmentation Methods

SEISM (Supervised Evaluation of Image Segmentation Methods) allows you to easily evaluate your segmentation method using the precision-recall for boundaries and the new precision-recall for objects and parts. You can download the code from GitHub.

The package is described in the following publications:

J. Pont-Tuset and F. Marques
Supervised Evaluation of Image Segmentation and Object Proposal Techniques
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI),
vol. 38, no. 7, pp. 1465-1478, 2016.
[PDF] [BibTeX]

@article{Pont-Tuset2016a,
  author = {Jordi Pont-Tuset and Ferran Marques},
  title = {Supervised Evaluation of Image Segmentation and Object Proposal Techniques},
  journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year = {2016},
  volume = {38},
  number = {7},
  pages = {1465--1478}
}

J. Pont-Tuset and F. Marques
Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation
Computer Vision and Pattern Recognition (CVPR) 2013
[PDF] [BibTex]

@inproceedings{PM2013,
  author = {Pont-Tuset, J. and Marques, F.},
  title = {Measures and Meta-Measures for the Supervised Evaluation of Image Segmentation},
  booktitle = {Computer Vision and Pattern Recognition},
  year = {2013}
}

Please cite these papers if you found the resources of this web useful.

BSDS500

The resources in this website are complementary to the BSDS500, which can be found here and was introduced in the following publication:

P. Arbeláez, M. Maire, C. Fowlkes, and J. Malik
Contour Detection and Hierarchical Image Segmentation
IEEE TPAMI, Vol. 33, No. 5, pp. 898-916, May 2011
[Project Page]

Code

Package to reproduce this work

BSDS500