Hi,
I am trying to build image search engine that would allow searching for image/part of the image inside a large database of images.
The plan is following:
1) Index all database images by extracting their SURF feature descriptors
2) Extract SURF descriptors from the file we want to find
3) Find the best match inside a database
I am stuck in a 3) where I cannot perform really fast search inside a database. Approaches like "Feature Matching with FLANN" work, but are slow and unscalable on large datasets.
Please point me to the right direction on how to: 1) perform a really fast search 2) prepare SURF descriptors so that they could be indexed (the size of outgoing descriptors varies from image to image, and I guess needs to be normalized somehow)