Title :
A survey of face recognition algorithms and testing results
Author :
Barrett, William A.
Author_Institution :
Nat. Biometrics Test Center, San Jose State Univ., CA, USA
Abstract :
Automated face recognition (AFR) has received increased attention. We describe two general approaches to the problem and discuss their effectiveness and robustness with respect to several possible applications. We also discuss some issues of run-time performance. The AFR technology falls into three main subgroups, which represent more-or-less independent approaches to the problem: neural network solutions, eigenface solutions, and wavelet/elastic matching solutions. Each of these first requires that a facial image be identified in a scene, a process called segmentation. The image should be normalized to some extent. Normalization is usually a combination of linear translation, rotation and scaling, although the elastic matching method includes spatial transformations.
Keywords :
face recognition; image matching; image segmentation; neural nets; wavelet transforms; automated face recognition; eigenface solutions; face recognition algorithms; image segmentation; linear translation; neural network solutions; normalization; rotation; run-time performance; scaling; spatial transformations; survey; testing results; wavelet/elastic matching; Biometrics; Face detection; Face recognition; Image databases; Image segmentation; Layout; Mouth; Neural networks; Testing; Vectors;
Conference_Titel :
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-8316-3
DOI :
10.1109/ACSSC.1997.680208