Title :
Face detection based on improved AdaBoost algorithm in E-Learning
Author :
Wansen Wang ; Huifang Niu
Author_Institution :
Capital Normal Univ., Beijing, China
fDate :
Oct. 30 2012-Nov. 1 2012
Abstract :
This paper is based on the background of learners´ expression recognition in emotion recognition interactive E-Learning. This paper aims at time-consuming of training samples and weights degradation two problems of traditional AdaBoost algorithm, proposes a decile eigenvalue AdaBoost algorithm and joins FPR (False Positive Rate) in this algorithm. The experiments use improved AdaBoost algorithm in E-Learning face detection achieved good effect, and the results provide good conditions for the follow-up E-Learning expression feature extraction.
Keywords :
computer aided instruction; emotion recognition; face recognition; feature extraction; image classification; learning (artificial intelligence); object detection; decile eigenvalue AdaBoost algorithm; e-learning expression feature extraction; electronic learning; emotion recognition interactive e-learning; face detection; false positive rate; improved AdaBoost algorithm; joins FPR; learners expression recognition; Algorithm design and analysis; Classification algorithms; Electronic learning; Face; Face detection; Feature extraction; Training; AdaBoost algorithm; E-Learning; FPR; Face detection; eigenvalue;
Conference_Titel :
Cloud Computing and Intelligent Systems (CCIS), 2012 IEEE 2nd International Conference on
Conference_Location :
Hangzhou
Print_ISBN :
978-1-4673-1855-6
DOI :
10.1109/CCIS.2012.6664311