So, I wrote a code for a SIFT/SURF+BOVW+SVM Classifier for 20 kinds of texture in Python. In method train(), I extract SIFT/SURF feature descriptors for every image in my training set, and I have created a BOWKMeansTrainer as follows:
dictionarySize = 20
BOW = cv.BOWKMeansTrainer(dictionarySize)
I have 80 training images.
So, I add the descriptors of each image to BOW like:
kp,desc=surf(img)
BOW.add(desc)
All of these form a dictionary with size (20,64). What does this 64 mean?
And, how does the BOW trainer know that some image x belongs to class c? What data do I feed into the SVM?
Help in understanding this would be greatly appreciated.
Thanks
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