Study of The Cost-sensitive AdaBoost Face Detection Algorithm

摘要：

It is the mainstream method that in human face detection and recognition with AdaBoost as the representative based on statistical learning method. Detection rates have reached a high level, and can achieve real-time detection. However, AdaBoost algorithm treats equally for different categories, there is no distinction between the cost of the different error categories. This paper presents a new cost-sensitive Ada Boost-based face detection algorithm, ensuring the detection rate and speed, effectively reducing the false detection rate, and improving the detection accuracy.

关键词： cost-sensitive face detection cascade classifier adaboost

作者: Dingli Song BingruYang FuxingYu

作者单位: School of Information Engineering University of Science and Technology Beijing Beijing, China Colleg School of Information Engineering University of Science and Technology Beijing Beijing, China College of Computer and Automatic Control Hebei Polytechnic University

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 335-338

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）