我开始在开放式中心。 我发现,我已经成功面对,现在我正试图做的是,从两个不同的图像中调和脸谱,归还真实或虚假的价值。 如何在使用++的开放式中心这样做?
Face recognition is an advanced method.
There is a website devoted for this : http://www.face-rec.org/
它包含许多研究论文、算法等,以面对承认。 你可以发现类似地点。
Two popular method used for this purposes are:
1. Eigen faces:
理解这一点,以下维基百科的通过是好的:
A set of eigenfaces can be generated by performing a mathematical process called principal component analysis (PCA) on a large set of images depicting different human faces. Informally, eigenfaces can be considered a set of "standardized face ingredients", derived from statistical analysis of many pictures of faces. Any human face can be considered to be a combination of these standard faces. For example, one s face might be composed of the average face plus 10% from eigenface 1, 55% from eigenface 2, and even -3% from eigenface 3. Remarkably, it does not take many eigenfaces combined together to achieve a fair approximation of most faces. Also, because a person s face is not recorded by a digital photograph, but instead as just a list of values (one value for each eigenface in the database used), much less space is taken for each person s face.
First 32 eigen face of a face (obtained from 。
可在。
2. Fisher Faces:
This uses another method called Linear Discriminant Analysis. For more details visit: http://www.scholarpedia.org/article/Fisherfaces
例如:第一4名渔民面临形象
<><>Finally, 您可在上找到其C++的实施工作。 ∗∗∗∗∗
For your information, the above implementation has been added to OpenCV mainstream from version 2.4-beta onwards (View changelog here). Even the codes are included in cpp samples that come with OpenCV 2.4-beta.
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