电子科技大学学报Issue(4)：589-593,5.DOI:10.3969/j.issn.1001-0548.2015.04.019
AdaBoost人脸检测定点型优化算法
Fixed-Point Optimization Algorithm of AdaBoost Face Detection
摘要
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, the computing process of the weak classifiers and the strong classifiers is effectively decomposed, 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 according to the accuracy requirements of the floating point calculation of strong classifiers, the proposed algorithm realizes the classifier calculation and the transformation of related model parameters. The AdaBoost algorithm has the calculation accuracy approximate to that of the original floating-point algorithm and therefore maintains the higher accuracy of face detection, which will be beneficial for the optimization of SIMD parallel computing method and the transplantation and optimization of the algorithm in the fixed point type of embedded equipments.关键词
AdaBoost/人脸检测/图像积分图/强分类器/弱分类器Key words
AdaBoost/face detection/integral image/strong classifier/weak classifier分类
信息技术与安全科学引用本文复制引用
周振华..AdaBoost人脸检测定点型优化算法[J].电子科技大学学报,2015,(4):589-593,5.
