Incorporating multiple distance spaces in optimum-path forest classification to improve feedback-based learning

@article{Silva2012IncorporatingMD,
  title={Incorporating multiple distance spaces in optimum-path forest classification to improve feedback-based learning},
  author={Andr{\'e} Tavares da Silva and Jefersson Alex dos Santos and Alexandre X. Falc{\~a}o and Ricardo da Silva Torres and L{\'e}o Pini Magalh{\~a}es},
  journal={Computer Vision and Image Understanding},
  year={2012},
  volume={116},
  pages={510-523}
}
In content-based image retrieval (CBIR) using feedback-based learning, the user marks the relevance of returned images and the system learns how to return more relevant images in a next iteration. In this learning process, image comparison may be based on distinct distance spaces due to multiple visual content representations. This work improves the retrieval process by incorporating multiple distance spaces in a recent method based on optimum-path forest (OPF) classification. For a given… CONTINUE READING

Citations

Publications citing this paper.
Showing 1-10 of 10 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 76 references

A

  • M. Everingham, L. V. Gool, C.K.I. Williams, J. Winn
  • Zisserman, The PASCAL Visual Object Classes…
  • 2010
Highly Influential
7 Excerpts

J

  • C. Ferreira
  • dos Santos, R.daS. Torres, M. Gonçalves, R…
  • 2011
Highly Influential
8 Excerpts

A new CBIR approach based on relevance feedback and optimumpath forest classification

  • A. T. Silva, A. X. Falcão, L. P. Magalhães
  • J. WSCG 18 (1–3)
  • 2010
Highly Influential
20 Excerpts

Similar Papers

Loading similar papers…