Face detection based on improved AdaBoost algorithm in E-Learning

Wan-sen Wang, Huifang Niu
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引用次数: 3

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.
基于改进AdaBoost算法的在线学习人脸检测
本文以情感识别交互式电子学习中学习者表情识别为研究背景。针对传统AdaBoost算法训练样本耗时和权值退化两个问题,提出了一种十分位数特征值AdaBoost算法,并将FPR (False Positive Rate)加入到该算法中。实验中使用改进的AdaBoost算法进行E-Learning人脸检测取得了良好的效果,结果为后续的E-Learning表情特征提取提供了良好的条件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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