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OpenCV中Haarcascade xml文件的说明

[英]Explanation of haarcascade xml files in opencv

I'm working on a project for which I require high accuracy for face detection. 我正在做一个需要对人脸检测具有较高准确性的项目。 For detection I'm using opencv with python. 为了进行检测,我将python与opencv一起使用。

I'm still not able to achieve my target so I was thinking of manipulating the fields/data in the xml files - haarcascade_frontalface_default.xml and haarcascade_frontalface_alt2.xml. 我仍然无法实现目标,因此我正在考虑处理xml文件中的字段/数据-haarcascade_frontalface_default.xml和haarcascade_frontalface_alt2.xml。

However, I was unable to understand the tags in it. 但是,我无法理解其中的标签。 I want a brief explanation of the major tags only. 我只想简要解释主要标签。

Personally I used in more than one occasion the standard opencv's classifiers and they worked fine for me. 我个人曾多次使用标准opencv的分类器,它们对我来说效果很好。

But there are a lot of features that could make this classifiers not the best choice for you, like for example the pose of the face (common problem), the excessive luminosity in the captured frame, etc. 但是有很多功能可能会使此分类器不是您的最佳选择,例如面部姿势(常见问题),所捕获帧中的过度发光等等。

You can try to create your own classifier ( http://docs.opencv.org/trunk/d7/d8b/tutorial_py_face_detection.html ): 您可以尝试创建自己的分类器( http://docs.opencv.org/trunk/d7/d8b/tutorial_py_face_detection.html ):

  1. with an existing dataset (here you can choose the best one that fits for your goal based on the explanations http://www.face-rec.org/databases/ ) 使用现有的数据集(您可以在http://www.face-rec.org/databases/的说明下选择最适合您目标的数据集)
  2. or with a custom dataset with pictures (a lot of) taken by you in similar conditions of when your application has to detect the face 或使用自定义数据集,其中包含您在应用程序必须检测面部时的类似情况下所拍摄的图片(很多)

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