Title :
Frontal face localization using linear discriminant
Author :
Meng, Lingmin ; Nguyen, Truong Q.
Author_Institution :
Dept. of Electr. & Comput. Eng., Boston Univ., MA, USA
Abstract :
This paper introduces a novel face detection approach using linear discriminant to detect frontal faces in grayscale images. By modelling both faces and clutters as Gaussian distributions, an optimal discriminant template is developed to minimize the detection Bayesian error. Our simulation indicates that the proposed approach outperforms conventional template-based methods such as matched filter and eigenface methods.
Keywords :
Bayes methods; Gaussian distribution; covariance analysis; digital simulation; face recognition; optimisation; Bayesian error reduction; Gaussian distributions; clutter; covariance; eigenface methods; face detection; face recognition; frontal face localization; grayscale images; linear discriminant; matched filter; modelling; optimal discriminant template; simulation; Bayesian methods; Computer security; Emotion recognition; Face detection; Face recognition; Gray-scale; Hidden Markov models; Image databases; Image recognition; Solid modeling;
Conference_Titel :
Signals, Systems, and Computers, 1999. Conference Record of the Thirty-Third Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-7803-5700-0
DOI :
10.1109/ACSSC.1999.832428