摘要
针对常规基于肤色检测的Ada Boost算法的不足,提出了一种改进的Ada Boost人脸检测算法,算法包括人体肤色模型、人脸运动检测模型、改进的背景提取方法、针对人脸区域的光照增强方法。算法综合利用了人体肤色信息和人脸运动信息,能有效缩小搜索范围。实验结果表明,该方法与常规基于肤色检测的Ada Boost方法相比,在保证检测性能的基础上,有效提高了检测速度。
In order to overcome shortcomings of traditional skin detection based Ada Boost methods, an improved face detection method which is based on Ada Boost algorithm is proposed, including human skin model, motion detection, an optimized background extraction algorithm and an illumination enhancement method that only process face regions. This method can effectively decrease search scope using information of human skin and face motion in detected videos. Experimental results show that this approach could achieve higher speed and better detection performance compared to normal skin detection based Ada Boost algorithms.
出处
《计算机工程与应用》
CSCD
北大核心
2016年第11期209-214,共6页
Computer Engineering and Applications
基金
国家科技支撑计划(No.2013BAH09F01)
上海市科委科技创新行动计划(No.14511106900)
关键词
人脸检测
肤色模型
运动检测
face detection
skin model
motion detection