Face recognition with eigenfaces

Author

Zhujie ; Yu, Y.L.

Author_Institution

Dept. of Electr. & Electron. Eng., Hong Kong Univ. of Sci. & Technol., Kowloom, Hong Kong

fYear

1994

fDate

5-9 Dec 1994

Firstpage

434

Lastpage

438

Abstract

Develops an approach to face recognition using eigenfaces, focusing on the effects of the eigenface used to represent a human face under several environment conditions. The authors first derive some computational feasible formula to find the eigenfaces, then investigate the relationship of mean absolute error between original face images and reconstructed images under various conditions such as face size, lighting and head orientation changes. The experimental results show that a large number of eigenfaces are not necessary to describe an individual face and only about 80 eigenfaces are sufficient for a large size set of face images. Gaussian smoothing can minimize the error under the same conditions. Finally, a face recognition system with eigenfaces and backpropagation neural network is implemented

Keywords

backpropagation; face recognition; image recognition; image reconstruction; neural nets; smoothing methods; Gaussian smoothing; backpropagation neural network; eigenfaces; face recognition; face size; head orientation; human face; lighting; mean absolute error; reconstructed images; Backpropagation; Computer errors; Eigenvalues and eigenfunctions; Face detection; Face recognition; Head; Humans; Image reconstruction; Neural networks; Smoothing methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Industrial Technology, 1994., Proceedings of the IEEE International Conference on

Conference_Location

Guangzhou

Print_ISBN

0-7803-1978-8

Type

conf

DOI

10.1109/ICIT.1994.467155

Filename

467155