I'm new to machine learning. I'm doing a project by using opencv open source library. My issue is that I don't have experience in开发者_StackOverflow Machine Learning. I have extracted features from different images and I have evaluated them, now I want to classify objects in those images by using SVM but I don't know what to do. BTW, I used 3 different feature extractors, SIFT, SURF and FAST feature detector (with their descriptors)
Can you give me the guide and some examples to classify more than 5 objects in the background, such as coffee cups, coca cola, basket balls etc...
I'm doing my project in C++, environment (UBUNTU).
With the information provided, all I can give you is the following list:
- category-level classification tutorial from the CVML2011 summer school. It includes code (for you unfortunately in Matlab) which can help you to understand the concept behind it.
- paper called "A Practical Guide to Support Vector Classification" which clearly explains how to prepare the data, train and test SVM
- and of course the OpenCV documentation on svm training
As already pointed out by @jillesdewit you should try to be more specific.
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