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An embedded HMM-based approach for face detection and recognition

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2 Author(s)
Nefian, A.V. ; Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA ; Hayes, M.H.

We describe an embedded hidden Markov model (HMM)-based approach for face detection and recognition that uses an efficient set of observation vectors obtained from the 2D-DCT coefficients. The embedded HMM can model the two dimensional data better than the one-dimensional HMM and is computationally less complex than the two-dimensional HMM. This model is appropriate for face images since it exploits an important facial characteristic: frontal faces preserve the same structure of “super states” from top to bottom, and also the same left-to-right structure of “states” inside each of these “super states”

Published in:

Acoustics, Speech, and Signal Processing, 1999. Proceedings., 1999 IEEE International Conference on  (Volume:6 )

Date of Conference:

15-19 Mar 1999

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