基于OpenCV的人脸检测 毕设论文 - 图文(8)

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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参考文献

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