Bag-of-Features Descriptor on SIFT ORB SURF (BoF-SIFT)

参考：http://www.codeproject.com/Articles/619039/Bag-of-Features-Descriptor-on-SIFT-Features-with-O

SIFT - Scale Invariant Feature Transform

Bag-of_Features with SIFT

Let's see how can we build BoF with SIFT features.

• 1. Obtain the set of bags of features.
  1. Select a large set of images.
  2. Extract the SIFT feature points of all the images in the set and obtain the SIFT descriptor for each feature point that is extracted from each image.
  3. Cluster the set of feature descriptors for the amount of bags we defined and train the bags with clustered feature descriptors (we can use the K-Means algorithm).
  4. Obtain the visual vocabulary.
• 2. Obtain the BoF descriptor for given image/video frame.
  5. Extract SIFT feature points of the given image.
  6. Obtain SIFT descriptor for each feature point.
  7. Match the feature descriptors with the vocabulary we created in the first step
  8. Build the histogram.

The following image shows the above two steps clearly. (The image taken from http://www.sccs.swarthmore.edu/users/09/btomasi1/tagging-products.html)