AdaBoost人脸检测定点型优化算法：Fixed point based optimization algorithm for face detection in AdaBoost.pdf

第 44 卷第 4 期电子科技大学学报
2015年7月 Journal of University of Electronic Science and Technology of China Jul. 2015
AdaBoost人脸检测定点型优化算法
周振华
(河南省水文水资源局郑州 450003)

【摘要】提出一种AdaBoost人脸检测的定点型优化算法,该算法以AdaBoost人脸检测原型算法为基础,分析了Cascade瀑
布式级联分类器中弱分类器与强分类器分类计算的特点,有效分解了弱分类器与强分类器的计算过程,从而现实了强分类器
与弱分类器相关模型参数有效分离标定。优化算法进一步利用图像积分图及弱分类器计算特点,完成对弱分类器计算过程及
相关模型参数的定点型转化;同时,利用强分类器浮点的计算精度要求,完成强分类器计算过程及相关模型参数的定点型转
化。该定点型AdaBoost人脸检测方法计算精度逼近原浮点型算法计算精度,保持了较高的人脸检测正确率,并利于后期的SIMD
并行计算方法优化,同时,也利于算法在定点型嵌入式设备上的移植与优化。
关键词 AdaBoost; 人脸检测; 图像积分图; 强分类器; 弱分类器
中图分类号 文献标志码 A doi:.1001-

Fixed-Point Optimization Algorithm of AdaBoost Face Detection

ZHOU Zhen-hua
(Hydrology and Water Resources Bureau of Henan Province Zhengzhou 450003)

Abstract A new fixed-point optimized algorithm for AdaBoost face detection is proposed. Based on the
AdaBoost face detection prototype algorithm, the characteristics of classification calculation of the weak classifiers
and strong classifiers in waterfall cascade classifier is analyzed, puting process of the weak classifiers and
the strong classifiers is effectively posed, and the effective separation and calibration of the model
parameters of the strong classifiers and the weak classifiers are realized. By using integral image and the
calculation characteristics of the weak classifier and accor