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Carnegie Mellon Robotics Institute

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Abstract

This paper evaluates face recognition applied to the real-world application of Facebook. Because papers usually present results in terms of accuracy on constrained face datasets, it is difficult to assess how they would work on natural data in a real-world application. We present a method to automatically gather and extract face images from Facebook, resulting in over 60,000 faces datasets, we evaluate a variety of well-known face recognition algorithms (PCA, LDA, ICA, SVMs) against holistic performance metrics of accuracy, speed, memory usage, and storage size. SVMs perform best with ~65% accuracy, but lower accuracy algorithms such as IPCA are orders of magnitude more efficient in memory consumption and speed, yielding a more feasible system.

Keywords

face recognition, survey of approaches, social networking, real-world datasets

Notes

Grant ID: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4813471&isnumber=4813301

Number of pages: 6

Text Reference

Brian Becker and Enrique Ortiz, "Evaluation of face recognition techniques for application to facebook," 8th IEEE International Conference on Automatic Face & Gesture Recognition, 2008 (FG '08)., December, 2009.

BibTeX Reference

@inproceedings{Becker_2009_6502,
   author = "Brian Becker and Enrique Ortiz",
   title = "Evaluation of face recognition techniques for application to facebook",
   booktitle = "8th IEEE International Conference on Automatic Face & Gesture Recognition, 2008 (FG '08).",
   publisher = "IEEE",
   address = "http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4813471&isnumber=4813301",
   month = "December",
   year = "2009",
}

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