图6-4 在Release下运行\
图6-5 在Release下运行无误，运行\
6.2.1 为VC++ 2008 Express配置OpenCV环境
(1)打开VC++ 2008 Express，菜单 Tools -> Options -> Projects and Solutions -> VC++
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Directories
①Show directories for选择include files，加入目录 D:\\Program Files\\OpenCV2.0\\vc2008\\include\\opencv
②Show directories for选择library files，加入目录 D:\\Program Files\\OpenCV2.0\\vc2008\\lib 关闭VC++ 2008 Express。 (2)使用OpenCV 2.0编程
①打开VC++ 2008 Express，创建一个Win32控制台程序opencvhello；
②选择Solution Explorer里的opencvhello项目，点击鼠标右键，选择Properties；
③为项目的Debug配置增加依赖的库：cxcore200d.lib cv200d.lib highgui200d.lib ④为项目的Release配置增加依赖的库：cxcore200.lib cv200.lib highgui200.lib ⑤编译运行附录里的例程（需要将lena.jpg文件放在项目目录下）。
6.3 实验结果
（1）单个人脸检测
总数1/漏检0/错检0 (2)多个人脸检测
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总数10/漏检3/错检0 (3)多个人脸检测
总数2/漏检0/错检0
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6.4 结论
从实验结果可以看出，这种检测人脸的方法的漏检率还是比较高的。从有限的实验结果来分析，漏检的原因主要在于待检测的人脸中眼睛部分不够清晰。这主要是因为训练集数量太少，而且非人脸样本比重偏低。事实上，世界上的非人脸样式要远远大于人脸样式，因此有足够多的非人脸样本，才能够让分类器对非人脸图案的“分辨”能力大大提高。
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