DocumentCode :
548521
Title :
Fully automatic and quickly facial feature point detection based on LK algorithm
Author :
Jian-zheng, Liu ; Zheng, Zhao
Author_Institution :
Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
fYear :
2011
fDate :
21-23 June 2011
Firstpage :
190
Lastpage :
194
Abstract :
To identify people\´s facial expressions, locating facial feature points in images of faces is an important stage. In this paper we present a method for fully automatic and quick detection of facial feature points in image sequences or videos using Gabor feature based boosted classifiers based on LK algorithm. There are many ways detecting face in complex background, we assume that the face has been identified. The detected face region is divided into several regions of interest, each of which contains one feature point or more. We selected several "best feature points" in every region of interest used LK algorithm. The proposed facial feature point detection method uses individual feature patch templates to detect points in these "best feature points". These feature models are GentleBoost templates built from both gray level intensities and Gabor wavelet features. We tested our method with several videos, and the method has achieved a recognition rate of 95%.
Keywords :
emotion recognition; face recognition; image classification; image sequences; object detection; wavelet transforms; Gabor feature based boosted classifiers; Gabor wavelet features; GentleBoost templates; LK algorithm; face region detection; facial expression identification; facial feature point detection method; facial feature point location; feature patch templates; gray level intensities; image sequences; Databases; Facial features; Feature extraction; Gabor filters; Pixel; Training; Videos;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Networked Computing and Advanced Information Management (NCM), 2011 7th International Conference on
Conference_Location :
Gyeongju
Print_ISBN :
978-1-4577-0185-6
Electronic_ISBN :
978-89-88678-37-4
Type :
conf
Filename :
5967543
Link To Document :
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