How to use SIFT/SURF as features for a machine learning algorithm?

Question

Im working on an automatic image annotation problem in which im trying to associate tags with images. For that im trying for SIFT features for learning. But the problem is a

Answer 1

You can represent single SIFT as "visual word" which is one number and use it as SVM input, I think it is what you need. It is usually done by k-means clustering.

This method is called "bag-of-words" and described in this paper.

Short presentation review of method.