摘要
用支持向量机建立新的核函数,使得该函数集集成无穷多个AdaBoost算法的弱分类器,最终形成强分类器。应用该强分类器进行人脸检测。实验结果表明,该方法的人脸检测率优于有限维AdaBoost算法,提高了检测精度。
Face detection is a basic and important research subject in the machine vision and pattern recognition, which has important application value in image, video retrieval, video monitoring, automatic face recognition and intelligent human-machine interaction etc. After long-term development, face detection method has made remarkable achievements, and is widely used in many of the research method. Based on support vector machine, a new kernel function was built, which contains infinite weak classifiers of AdaBoost algorithm, and those weak classifiers finally formed a strong classifier. The experimental results show that face detection rate based on this method is better than the limited AdaBoost algorithm, which improved the detection accuracy.
出处
《重庆理工大学学报(自然科学)》
CAS
2012年第3期104-108,共5页
Journal of Chongqing University of Technology:Natural Science
基金
云南省科技厅基金资助项目(2009CA027)