inverted-quantized k-means
C++ Matlab Other
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README.md

iqm

iqm stands for inverted-quantized k-means (IQ-means) and implements a method for fast approximate clustering.

Licence

iqm has a 2-clause BSD license. See file LICENSE for the complete license text.

Directory structure

iqm constists primarily of Matlab .m files, but also includes a number of .cpp files which are compiled as mex files to interface Matlab. The directory structure is:

/anim      animation of algorithm iterations on 2D example
/config    project configuration, including datasets, paths etc.
/disp      text/graphical display
/lib       generic utilities library
/quant     full set of learning, encoding, inversion and search methods
/sub       underlying code handling subspaces
/test      main test entry points
/util      specific utilities for this application

Requirements

iqm requires Matlab, an appropriate C++ compiler to compile mex files (e.g. gcc), yael library, and xio library.

Setup

After installing yael, choose a location on disk, say home, where to store datasets and output. Make one subfolder for each dataset with the name of the dataset, say sift, and copy the raw dataset files in a subfolder named raw. For instance, download the SIFT1M dataset and unzip its contents into

home/sift/raw/

iqm uses the specific filenames and file formats as given in the link above. A number of additional folders for output will be created automatically under home/sift/.

Finally, edit /config/local.m and adjust the location of home and yael to your local settings. Now you can try any of the samples under /test/. The mex files should compile automatically.

Citation

Please cite the following paper if you use this software.

Y. Avrithis, Y. Kalantidis, E. Anagnostopoulos, and I. Z. Emiris. Web-scale image clustering revisited. In Proceedings of International Conference on Computer Vision (ICCV 2015), Santiago, Chile, December 2015.