An Integrated System of Face Recognition
IEA/AIE '09 Proceedings of the 22nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: Next-Generation Applied Intelligence
A new manifold representation for visual speech recognition
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Real-time robot manipulation using mouth gestures in facial video sequences
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
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This paper proposes a PCA based method to reduce the dimensionality of DCT coefficients for visual only lip-reading systems. A three-stage pixel based visual front end is adopted. First, DCT or block-based DCT features are extracted. Second, Principal Component Analysis is applied for dimension reduction. Finally, all the feature vectors are normalized into a uniform scale. This work investigates this three-stage method, comparing with PCA and two DCT based approaches whose features are selected manually. In the latter manner, PCA coefficients are selected according to energy while the reduction of DCT coefficients leans to the left components in the left-top corner. Experiments prove that the dimension reduction task based on PCA does improve the recognition accuracy when the final dimension is below a certain value. They also show that DCT and block-based DCT work similarly for lip reading task, outperforming PCA slightly.