The Study of Face Recognition Based on the Large Samples

Author

Xia, Liu ; Tingjun, Li ; Wei, Jiao ; Qingchang, Guo

Author_Institution

Harbin Eng. Univ., Harbin

Volume

2

fYear

2008

fDate

19-20 Dec. 2008

Firstpage

259

Lastpage

263

Abstract

A improved face recognition method based on the large samples was proposed in the paper. The face and the eyes were detected using the Adaboost algorithm; and according to the distance and angle of the eyes, the accurate face could be gotten. For improving the robustness of face recognition against illumination, the face image was processed by the Retinex theory. The face feature was extracted using the Gabor wavelet. The similarity of the faces was detected by the cosine and distance of face feature vectors. The validity of the algorithm is testified by the experiments.

Keywords

Gabor filters; eye; face recognition; feature extraction; learning (artificial intelligence); object detection; wavelet transforms; Adaboost algorithm; Gabor wavelet; eye detection; face detection; face recognition method; feature extraction; feature vector; large image sample; retinex theory; Eyes; Face detection; Face recognition; Feature extraction; Independent component analysis; Kernel; Linear discriminant analysis; Principal component analysis; Scattering; Vectors; Gabor wavelet; Retinex theory; face detection; face recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence and Industrial Application, 2008. PACIIA '08. Pacific-Asia Workshop on

Conference_Location

Wuhan

Print_ISBN

978-0-7695-3490-9

Type

conf

DOI

10.1109/PACIIA.2008.156

Filename

4756776