Title

Evaluation Of Face Recognition Techniques For Application To Facebook

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 representing over 500 users. From these natural face 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. © 2008 IE.

Publication Date

12-1-2008

Publication Title

2008 8th IEEE International Conference on Automatic Face and Gesture Recognition, FG 2008

Number of Pages

-

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/AFGR.2008.4813471

Socpus ID

67650665519 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/67650665519

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