Frontal face detection using support vector machines and back-propagation neural networks

Author

Bassiou, N. ; Kotropoulos, C. ; Kosmidis, T. ; Pitas, I.

Author_Institution

Dept. of Informatics, Aristotle Univ. of Thessaloniki, Greece

Volume

1

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

1026

Abstract

Face detection is a key problem in building systems that perform face recognition/verification and model-based image coding. Two algorithms for face detection that employ either support vector machines or backpropagation feedforward neural networks are described, and their performance is tested on the same frontal face database using the false acceptance and false rejection rates as quantitative figures of merit. The aforementioned algorithms can replace the explicitly-defined knowledge for facial regions and facial features in mosaic-based face detection algorithms

Keywords

backpropagation; face recognition; learning automata; recurrent neural nets; backpropagation; computer vision; face detection; face recognition; face verification; false acceptance rates; false rejection rates; feedforward neural networks; frontal face database; model-based image coding; mosaic-based algorithms; performance; support vector machines; Backpropagation algorithms; Face detection; Face recognition; Feedforward neural networks; Image coding; Image databases; Neural networks; Spatial databases; Support vector machines; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 2001. Proceedings. 2001 International Conference on

Conference_Location

Thessaloniki

Print_ISBN

0-7803-6725-1

Type

conf

DOI

10.1109/ICIP.2001.959223

Filename

959223