PLS Face Identification (PFI)

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This software, called PLS Face Identification (PFI), implements the one-against-all face identification method proposed in [1] and [2] (the second is an extension of the first by adding new feature descriptors). This software allows researchers to compare face identification methods to our method using datasets other than those considered in our papers.

To facilitate its usage, we provide a small data set (a subset of the FERET dataset), inside the directory SampleData in the software package.  Upon request (e-mail to william@dcc.ufmg.br), we will make available the cropped samples and partition files used during our experimental validation in [1] and [2] using the FERET and FRGC datasets. Note: the feature descriptors that will be extracted for the FERET example provided are different from those used in the papers. Please, contact us to obtain the feature configuration used in our papers.

This implementation has been used as part of the papers written by Schwartz et al. [1] and [2]. We kindly ask you to cite these references upon the use of this software. Please refer to the following bibtex entries.

[1] Robson, Schwartz, William; Huimin, Guo,; Jonghyun, Choi,; S, Davis, Larry (2012)Face identification using large feature setsIn: Image Processing, IEEE Transactions on, 21 (4), pp. 2245–2255, 2012.

[2] Schwartz, W. R.; Guo, H.; Davis, L. S. (2010)A Robust and Scalable Approach to Face IdentificationIn: European Conference on Computer Vision,pp. 476-489, 2010.

Documentation

Information regarding the usage of the software can be found in its manual [pdf]. This software also provides an execution example inside the zip file.

References

You should cite the following article if you use this software in your work.

Igor Leonardo Oliveira Bastos; William Robson Schwartz: Assigning Relative Importance to Scene Elements. In: Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 1-8, 2017. (Type: Inproceedings | Links | BibTeX)

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