DocumentCode :
2866021
Title :
The Study and Implementation of Face Recognition and Tracking System
Author :
Chen, Kai ; Le Jun Zhao
Author_Institution :
East China Univ. of Sci. & Technol., Shanghai, China
fYear :
2009
fDate :
11-13 Dec. 2009
Firstpage :
1
Lastpage :
5
Abstract :
There´s some very important meaning in the study of realtime face recognition and tracking system for the video monitoring and artificial vision. The current method is still very susceptible to the illumination condition, non-real time and very common to fail to track the target face especially when partly covered or moving fast. In this paper, we propose to use boosted cascade combined with skin model for face detection and then in order to recognize the candidate faces ,they will be analyzed by the hybrid Wavelet, PCA and SVM method. After that, Meanshift and Kalman filter will be invoked to track the face. The experimental results show that the algorithm has quite good performance in terms of real-time and accuracy.
Keywords :
Kalman filters; computer vision; face recognition; principal component analysis; real-time systems; support vector machines; target tracking; video signal processing; wavelet transforms; Kalman filter; PCA; SVM method; artificial vision; boosted cascade; face detection; hybrid wavelet; illumination condition; meanshift; realtime face recognition; skin model; tracking system; video monitoring; Discrete wavelet transforms; Face detection; Face recognition; Filters; Principal component analysis; Signal processing algorithms; Skin; Support vector machines; Target tracking; Wavelet analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4507-3
Electronic_ISBN :
978-1-4244-4507-3
Type :
conf
DOI :
10.1109/CISE.2009.5366352
Filename :
5366352
Link To Document :
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