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One-Sample Face Recognition Using HMM Model of Fiducial Areas
One-Sample Face Recognition Using HMM Model of Fiducial Areas ... This paper describes an effective algorithm for recognition and verification with one sample image per class. ... Now HMM [102] is ...
Programming of 2D HMM for face recognition.
Programming of 2D HMM for face recognition. ... One-Sample Face Recognition Using HMM Model of Fiducial Areas. ... an effective algorithm for recognition and verification with one sample image per ...
One-Sample Face Recognition Using HMM Model of Fiducial Areas
One-Sample Face Recognition Using HMM Model of Fiducial Areas . ... This paper describes an effective algorithm forrecognition and verification with one sample image per class. It uses two dimensional discretewavelet transform (2D DWT) to extract features from images; and hidden Markov model (HMM)was used for training, recognition and ...
One-sample Face Recognition Using HMM Model of Fiducial Areas
One-sample Face Recognition Using HMM Model of Fiducial Areas . ... This paper describes an effective algorithm for recognition and verification with one sample image per class. It uses two dimensional discrete wavelet transform (2D DWT) to extract features from images; and hidden Markov model (HMM) was used for training, recognition and ......
Which is the best algorithm for Face Recognition?
Which is the best algorithm for Face Recognition? ... Face Recognition Using HMM Model of Fiducial Areas. ... an effective algorithm for recognition and verification with one sample image per ......
 Facial Expression Recognition using Efficient LBP and CNN
al.[8] proposed facial expression recognition method using Hidden Markov Model. The relative displacement of the feature points between the current frame and the neutral frame are extracted as the facial features. Classification entropy threshold and model parameters are found out using iterative algorithm during training process....
Face Recognition Homepage - Algorithms
X. Liu, T. Chen, Video-Based Face Recognition Using Adaptive Hidden Markov Models, Proc. of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2003, Vol. I, 16-22 June 2003, Madison, Wisconsin, USA, pp. 340-345
Applying Hidden Markov Model for Face Recognition using ...
active research sub-area of face recognition. Finding effective algorithms that deal with this problem is the goal of this dissertation. In order to achieve the goal of building a system recognizing face images, we need a model that can capture selective spatial information. In this dissertation, a Hidden Markov Model (HMM) [10]...
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