Eye Detection Based on Improved AD AdaBoost Algorithm

摘要：

Eye detection is an important step in eye tracking and eye state recognition. An improved AD AdaBoost algorithm for eye detection is proposed to slow the degradation in training step. Weight on negative samples which are classified correctly is released then the other samples weight is normalized to slow the expansion of weight on difficult samples. The experiment results show that the approach proposed is real time and has a higher detection accuracy.

关键词： Eye Detection AD AdaBoost Cascaded Classifier

作者: Benke Xiang Xiaoping Cheng

作者单位: College of Computer and Information Science Southwest University Chongqing P.R China

会议类型: 国际会议

会议名称: 2010 2nd International Conference on Signal Processing System(2010年信号处理系统国际会议 ICSPS 2010)

会议地点: 大连

会议语种:英文

页码: 1457-1460

在线出版日期: 2010-07-05（万方平台首次上网日期，不代表论文的发表时间）