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如何为SVM(EmguCV)创建培训集?

[英]How can I create a trainingsset for SVM (EmguCV)?

I´ve got several problems with my task. 我的任务有几个问题。 I want to implement an emotion recognizer. 我想实现一个情绪识别器。 After my long search for methods, I think a combination of a feature extractor like SURF or PCA combined with SVM could be a good idea. 在长期寻找方法之后,我认为将SURF或PCA之类的特征提取器与SVM结合使用可能是一个好主意。 I´ve implemented a detector for relevant parts of the face like mouth and eyes. 我已经为面部的相关部位(例如嘴和眼)安装了一个探测器。 And now I want to extract the features and store them as matrix. 现在,我想提取特征并将其存储为矩阵。

I know I have to create a training set and a test set of my collected images and preprare the training set for SVM. 我知道我必须为收集的图像创建一个训练集和一个测试集,并为SVM准备训练集。 And that´s my problem. 那是我的问题。

Which extractor will be the best? 哪个提取器是最好的? And does every extractor give a vector back with features? 每个提取器都提供具有特征的向量吗?

I don´t know how to start:-( How I get the features as a vector and save them as a matrix.... 我不知道如何开始:-(我如何将特征作为向量并将其保存为矩阵。

Sorry, I don´t have enough experiences in machine learning. 抱歉,我没有足够的机器学习经验。 I´m searching for many days to find the answer and I hope someone can give me advice.....thanks a lot. 我正在寻找答案的日子很多,希望有人能给我建议。。。非常感谢。

What you want to do is complicated, you should first focus on how SURF work, then how SVM work, and also have a look to Bag of Visual words. 您想要做的事情很复杂,您应该首先关注SURF的工作原理,然后是SVM的工作原理,然后看看“视觉包”一词。

First try to use SURF. 首先尝试使用SURF。 Most of "extractor" (SIFT, SURF, etc.) work in two time 1)detection - detecting interesting points 2)extraction - extract features. 大多数“提取器”(SIFT,SURF等)都在两次工作:1)检测-检测有趣的点2)提取-提取特征。 The problem is that you can't use SURF directly in SVM because one image have several points which have 64 or 128 features. 问题是您不能在SVM中直接使用SURF,因为一个图像具有多个具有64或128个要素的点。 The problem is that the number of points in each image can be different, and SVM need the same number of feature for each image. 问题在于每个图像中的点数可以不同,并且SVM对于每个图像需要相同数量的特征。 So you should have a look to Bag of Visual Words . 因此,您应该看一下“视觉单词袋”

SURF- Emgu tutorial SURF- Emgu教程

SVM - Emgu tutorial SVM-Emgu教程

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