A C++11 multithread library for image retrieval

This project is maintained by hlzz

libvot - A C++11 multi-thread library for image retrieval

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libvot is a fast implementation of vocabulary tree, which is an algorithm widely used in image retrieval and computer vision. It usually comprises three components to build a image retrieval system using vocabulary tree: build a k-means tree using sift descriptors from images, register images into the database, query images against the database. In this library, we use C++11 standard multi-thread library to accelerate the computation, which achieves fast and accurate image retrieval performance. Currently this library is under active development for research purpose. If you find this repository useful, please star it to let me know. :)


The build system of libvot is based on CMake. To take full advantages of the new features in C++11, we require the version of CMake to be 2.8.12 or above. Current we have tested our project under Linux (Ubuntu 14.04, CentOS 7) and MacOS (10.10) using gcc. The common steps to build the library are:

  1. Extract source files.
  2. Create build directory and change to it.
  3. Run CMake to configure the build tree.
  4. Build the software using selected build tool.
  5. Run "make test"
  6. See src/example for the usage of this library.

On Unix-like systems with GNU Make as the build tool, the following sequence of commands can be used to compile the source code.

$ cd libvot
$ git submodule init & git submodule update  
$ mkdir build && cd build
$ cmake ..
$ make && make test

Optional dependencies include OpenCV, but it is not required to run the core functions in libvot.

First try

Suppose $LIBVOT_ROOT represents the root directory of libvot, and it is successfully compiled in build subdirectory. You can use ./libvot_feature <image_list> to first generate a set of descriptor files and use them as inputs to image_search. For example, you have some target .jpg image files to generate sift files. Just cd into that directory, prepare the image_list, and generate sift files in the same directory as the image files:

$ ls -d $PWD/*.jpg > image_list
$ $LIBVOT_ROOT/build/bin/libvot_feature <image_list>

Then you can run image_search in src/example to generate the image retrieval results The usage is simply “./image_search [depth] [branch_num] [sift_type] [num_matches] [thread_num]”. We add a small image dataset fountain-P11 to illustrate this process. test_data/fountain_dense folder contains the sift files generated by libvot_feature, while the original images are not included in order to save space. If you use the out-of-source build as shown in the installation section and in the build directory, the following command should work smoothly and generate several output files in build/bin/vocab_out directory (you need to change the prefix of filepaths in test_data/fountain_dense/sift_list).

$ cd bin
$ ./image_search <sift_list> <output_folder> [depth] [branch_num] [sift_type] [num_matches] [thread_num]  
$ (e.g.) ./image_search ../../test_data/fountain_dense/sift_list ./vocab_out

Each line in match.out contains three numbers “first_index second_index similarity score”. Since the library is multi-threaded, the rank is unordered with respect to the first index (they are ordered w.r.t the second index). match_pairs saves the ordered similarity ranks, from 0th image to n-1th image. Besides, libvot also supports sift files generated by openMVG.


The homepage of libvot is hosted by github-pages. See the documentation here.


We are working toward the next major release (0.2.0). If you are interested in contributing, please have a look at All types of contributions, including documentation, testing, and new features are welcomed and appreciated.


The BSD 3-Clause License

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