@article {412,
	title = {The integration of PCA, FLD and gabor two-dimensional wavelet transformation using facial expression feature extraction},
	journal = {Journal of Digital Information Management},
	volume = {11},
	year = {2013},
	note = {Export Date: 10 July 2014},
	month = {2013},
	pages = {284 - 289},
	abstract = {In order to improve the rate of facial expression recognition. The Gabor wavelet fusion PCA+FLD method is proposed as a new method this paper. Firstly, face image preprocessing, and then carries on the two-dimensional wavelet transform Gabor, first constructed five scale eight directional wavelet filter, through the PCA+FLD method for dimensionality reduction, and finally obtaining an optimum expression a projection subspace classifier in all the optimal subspace. The experiment proves, fusion PCA, FLD and Gabor wavelet transform two-dimensional facial expression feature extraction for classifier design, facial expression recognition rate is high. The experiment proves that the new method of Gabor wavelet fusion PCA+FLD is perfect.},
	keywords = {Facial expression recognition, PCA+FLD, Two dimensional gabor wavelet},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84888357193\&partnerID=40\&md5=4efdf9679a3c503ac68ea63914484966},
	author = {Ni, J. and Li, Y.}
}
