Question

求这一段话翻译，要求准确，谢谢

针对复杂背景条件下人脸检测的检测率低速度慢的问题，选择了基于统计的人脸检测算法。本文详细介绍了AdaBoost 算法的基本原理，利用OpenCV 编程实现了基于AdaBoost 的人脸检测.深入分析了强分类器的个数及排序对检测器性能的影响。对 3 种分类方法得到的分级分类器的检测能力进行了比较，给出一个实用的分级分类器，并给出了用 OpenCV 实现人脸检测的核心程序。AdaBoost人脸检测算法最大的特点是识别效果好、实时性好、检测速度快，其检测速度不逊于目前公布的最快的算法。实验结果表明，用OpenCV 实现的AdaBoost检测器简单实用，开发周期短，应用前景广阔。

Answer 1

Given (that)the low of validity and speed in the face detection in complex background, (the writer)chooses an algorithm of face detection based on statistics. This paper introduces the basic principles about AdaBoost in details achieving a face detection based on AdaBoost by using OpenCV programme. The influences to the detector caused by the number of the strong classifier and the order of them are analyzed in depth. Compare the detectabilities of the classifier feed backed by three different ways of classification and produce a practical classifier and a core programme to achieve a face detection by using OpenCV. The best features of the algorithm of face detection AdaBoost are as following: good identification, good real-time, high speed of test. The speed of test is as well as the fastest algorithm nowadays. The experiment results show that AdaBoost detector is simple and practical which demands a short developing period with a vast application prospect.