DocumentCode :
2675077
Title :
Face tracking with an Adaptive Adaboost-based Particle Filter
Author :
Dou, Jianfang ; Li, Jianxun ; Zhang, Zhi ; Han, Shan
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fYear :
2012
fDate :
23-25 May 2012
Firstpage :
3626
Lastpage :
3631
Abstract :
A novel algorithm, termed a Boosted Adaptive Particle Filter (AAPF), for integrated face detection and face tracking is proposed. The proposed algorithm is based on the synthesis of an adaptive particle filtering algorithm and the AdaBoost face detection algorithm. An Adaptive Particle Filter (AAPF), based on a new sampling technique, is proposed. The APF is shown to yield more accurate estimates of the proposal distribution than the standard Particle Filter thus enabling more accurate tracking in video sequences. In the proposed AAPF algorithm, the AdaBoost algorithm is used to detect faces in input image frames, the APF algorithm incorporate the detection result of AdaBoost algorithm to improve the proposal distribution of the particles. Experimental results show that the proposed AAPF algorithm provides a means for robust face detection and accurate face tracking under various tracking scenarios.
Keywords :
face recognition; image sampling; image sequences; learning (artificial intelligence); object detection; object tracking; particle filtering (numerical methods); video signal processing; AAPF algorithm; AdaBoost face detection algorithm; adaptive Adaboost-based particle filter; adaptive particle filtering algorithm; boosted adaptive particle filter; face tracking; image frames; proposal distribution; sampling technique; video sequences; Color; Face detection; Histograms; Image color analysis; Particle filters; Proposals; Target tracking; Adaboost; Face detection; Particle filter; proposal distribution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
Type :
conf
DOI :
10.1109/CCDC.2012.6244580
Filename :
6244580
Link To Document :
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