OBINDEX is an open source C++ library for indexing images. It implements a hierarchical indexing scheme to match binary descriptors, which is used as an incremental Bag-Of-Words (BoW) visual vocabulary. This index is combined with an inverted file in order to provide an image database, that can be queried for finding similar images. This online binary visual vocabulary tries to solve the main drawbacks that classical BoW approaches present, avoiding the training step and adapting the visual dictionary to the operating environment.
OBINDEX is released as a ROS package, and relies on OpenCV, FLANN and Boost libraries. It can be used with any binary descriptor computed using the OpenCV format.
Note that OBINDEX is research code. The authors are not responsible for any errors it may contain. Use it at your own risk!
Our approach is detailed in:
On the Use of Binary Feature Descriptors for Loop Closure Detection
Emilio Garcia-Fidalgo and Alberto Ortiz
IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)
Barcelona (Spain), 2014
The paper can be downloaded from [here] (http://emiliofidalgo.github.io/static/papers/conf_ETFA_Garcia2014.pdf). If you use this software in an academic work, please cite:
@INPROCEEDINGS{GarciaFidalgoETFA14,
author={Garcia-Fidalgo, Emilio and Ortiz, Alberto},
booktitle={Emerging Technology and Factory Automation (ETFA), 2014 IEEE},
title={On the use of binary feature descriptors for loop closure detection},
year={2014},
month={Sept},
pages={1-8},
doi={10.1109/ETFA.2014.7005121}
}
OBINDEX is distributed under the terms of the [BSD License] (http://github.com/emiliofidalgo/obindex/blob/master/LICENSE).
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First of all, you will need to have installed all library dependencies:
sudo apt-get install libflann-dev
sudo apt-get install libboost-system-dev
sudo apt-get install libboost-filesystem-dev -
Clone the repository into your workspace:
cd ~/your_workspace/src
git clone https://github.com/emiliofidalgo/obindex.git -
Compile the package using
catkin_make:cd ..
catkin_make -DCMAKE_BUILD_TYPE=Release -
You can run an example:
rosrun obindex test_bindex /directory/of/images
For an example of use, see the demo file (src/demo/example.cpp).
Currently, the memory allocation is performed during the class initialization and not dynamically. This implies that you should indicate as a parameter (max_descriptors) the approximate number of descriptors that you need to index. See the demo file (src/demo/example.cpp) to see an example of how to set this parameter.
If you have problems or questions using the library, please contact the authors (emilio.garcia@uib.es). Improvements are totally welcome.