基于Adaboost算法的人脸检测及OpenCV实现

Face detection Based on Adaboost algorithm and OpenCV

人脸检测是人脸识别等人脸信息处理系统中的关键问题。基于学习的方法中,Adaboost算法的级联检测器结构计算效率高,可以有效检测图像中的人脸。应用开源计算机视觉库(OpenCV)开发了人脸检测系统,该系统给出了直观的人机交互界面,先装载人脸检测分类器,再运用Adaboost算法检测图像中出现的人脸,并用椭圆框标示人脸。文中介绍了Adaboost目标检测算法和系统实验结果,实验结果表明,在OpenCV基础上,采用Adaboost算法可以快速、准确的实现人脸检测。

Face detection is the key issues in face recognition and other face information processing system. The cascade detector structure of Adaboost algorithm calculation efficiency, it can effectively detect the face in image. Face detection system with Open Source Computer Vision Library(OpenCV) is developed, the system has intuitive human-compute interaction interface,first, load the face detection classifier, and then, using Adaboost algorithm to detect face in images, and ellipses labeled faces. This paper introduced the Adaboost target detection algorithm and experimental results of the system. The experimental results show that the Adaboost algorithm can quickly, accurately realize the face detection using OpenCV.