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
Copyright Status
Unknown
Socpus ID
67650665519 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/67650665519
STARS Citation
Becker, Brian C. and Ortiz, Enrique G., "Evaluation Of Face Recognition Techniques For Application To Facebook" (2008). Scopus Export 2000s. 9631.
https://stars.library.ucf.edu/scopus2000/9631