What I have so far
I have a set of images that I am trying to classify. I can also extract different feature descriptors from the images using algorithms such as hu moments, color histogram, and SIFT. I can the build a vocabularies from each of these algorithms.
What I do not understand is how can I combine these vocabularies together. From my understanding these feature descriptors can be of different size depending on what the features are. What would be the proper way to build this vocabulary from these different algorithms.
What is confusing me is how would we be combining feature descriptors from different algorithms which have different sizes? SIFT will give a m x 128 array where m is the number of feature descriptors of set size 128. A color histogram may give a count of each color in the range of 0-255. How would I combine these two in a meaningful way?
Here is the paper I was reading which gave me the idea of combining the vocabularies.
Here is what I was reading before:
If anyone can point me in the right direction I would greatly appreciate it.