Introduction - If you have any usage issues, please Google them yourself
This C++/Matlab package implements several algorithms used for large scale
image search. The algorithms are implemented in C++, with an eye on large
scale databases. It can handle millions of images and hundreds of millions
of local features. It has MEX interfaces for Matlab, but can also be used
(with possible future modifications) from Python and directly from C++. It
can also be used for approximate nearest neighbor search, especially using
the Kd-Trees or LSH implementations.
The algorithms can be divided into two broad categories, depending on the
approach taken for image search:
1. Bag of Words:
----------------
The images are represented by histograms of visual words.
It includes algorithms for computing dictionaries:
* K-Means.
* Approximate K-Means (AKM).
* Hierarchical K-Means (HKM).
It also includes algorithms for fast search:
* Inverted File Index.
* Inverted File Index with Extra Information (for example for implementing
Hamming Embedding).
*