Question

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 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).

Answer 1

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.