Fast face recognition method using high order autocorrelations

Author

Goudail, F. ; Lange, Eberhard ; Iwamoto, Takashi ; Kyuma, Kazuo ; Otsu, Nobuyuki

Author_Institution

Central Res. Lab., Mitsubishi Electr. Corp., Hyogo, Japan

Volume

2

fYear

1993

fDate

25-29 Oct. 1993

Firstpage

1297

Abstract

We describe both the implementation and the evaluation of a face recognition method. The feature extraction algorithm is based on the computation of local autocorrelation coefficients. The main characteristics of these coefficients are simplicity of computation and a built-in translational invariance, which allows the system to respond in real time. The classification is realized by conventional methods; namely least square discriminant mapping and linear discriminant analysis, which may be implemented with hardware neural networks. We tested the system on a database of 11600 images of 116 persons. The simulations show peak recognition rates of up to 98% and a satisfactory rejection vs. recognition ratio.

Keywords

correlation methods; face recognition; feature extraction; image classification; least squares approximations; neural nets; built-in translational invariance; classification; fast face recognition method; feature extraction algorithm; high-order autocorrelations; least square discriminant mapping; linear discriminant analysis; local autocorrelation coefficients; peak recognition rates; Autocorrelation; Face recognition; Feature extraction; Image databases; Least squares methods; Linear discriminant analysis; Neural network hardware; Neural networks; Real time systems; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1993. IJCNN '93-Nagoya. Proceedings of 1993 International Joint Conference on

Print_ISBN

0-7803-1421-2

Type

conf

DOI

10.1109/IJCNN.1993.716783

Filename

716783