Face detection and recognition using hidden Markov models

Author

Nefian, Ara V. ; Hayes, Monson H., III

Author_Institution

Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA, USA

Volume

1

fYear

1998

fDate

4-7 Oct 1998

Firstpage

141

Abstract

The work presented in this paper describes a hidden Markov model (HMM)-based framework for face recognition and face detection. The observation vectors used to characterize the states of the HMM are obtained using the coefficients of the Karhunen-Loeve transform (KLT). The face recognition method presented reduces significantly the computational complexity of previous HMM-based face recognition systems, while slightly improving the recognition rate. Consistent with the HMM model of the face, this paper introduces a novel HMM-based face detection approach using the same feature extraction techniques used for face recognition

Keywords

Karhunen-Loeve transforms; computational complexity; face recognition; feature extraction; hidden Markov models; HMM; Karhunen-Loeve transform coefficients; computational complexity reduction; face detection; face recognition; feature extraction; hidden Markov models; observation vectors; recognition rate; Face detection; Face recognition; Feature extraction; Hidden Markov models; Image databases; Image processing; Karhunen-Loeve transforms; Probability density function; Robustness; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on

Conference_Location

Chicago, IL

Print_ISBN

0-8186-8821-1

Type

conf

DOI

10.1109/ICIP.1998.723445

Filename

723445