Title :
Hidden Markov models for face recognition
Author :
Nefian, Ara V. ; Hayes, Monson H., III
Author_Institution :
Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA
Abstract :
The work presented in this paper focuses on the use of hidden Markov models for face recognition. A new method based on the extraction of 2D-DCT feature vectors is described, and the recognition results are compared with other face recognition approaches. The method introduced reduces significantly the computational complexity of previous HMM-based face recognition system, while preserving the same recognition rate
Keywords :
computational complexity; discrete cosine transforms; face recognition; feature extraction; hidden Markov models; 2D-DCT feature vectors extraction; HMM; computational complexity reduction; face recognition; hidden Markov models; recognition rate; recognition results; Computational complexity; Face recognition; Feature extraction; Hidden Markov models; Image processing; Image recognition; Probability density function; Signal processing; Speech recognition; Virtual manufacturing;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.678085
