open source code for loop closure detection, binary feature based.
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MILD
ORBSLAM
data
.gitignore
.gitignore~
CMakeLists.txt
MILD.config
MILD.creator
MILD.creator.user
MILD.files
MILD.includes
README.md
evaluation.m
frame.cpp
frame.h
global.h
imagelist.txt
main.cpp
run_scritp.m
settings.yaml

README.md

MILD

Project for MILD: An efficient loop closure detection libary based on binary features.

Related papers:

  1. Multi-Index Hashing for Loop closure Detection. International Conference on Multimedia Expo, 2017. Best Student Paper Awards.

  2. Beyond SIFT Using Binary features in Loop Closure Detection. IROS 2017.

Prerequisites

Ubuntu 14.04

cmake 3.2.0

OpenCV 3.1 http://xfloyd.net/blog/?p=987

eigen3

octave (optional, only used for evaluation)

Installation

$ mkdir build

$ cd build

$ cmake ..

$ make

Usage

./mild imagelist.txt settings.yaml

input:

imageList.txt: indicats the path of each input RGB image per line settings.yaml: indicats the parameters used in loop closure detection

output:

output/imagelist/lcd_shared_flag.bin: detected loop closure are set as 1. To be used in the run_scritp.m to check the accuracy of the detected loop closure. output/imagelist/lcd_shared_score_mild.bin: the image similarity calculated using MILD. output/imagelist/relocalization_time_per_frame.bin: lcd time of each frame.

evluation: (based on MATLAB/OCTAVE)

evaluation('build/output/imageList_NewCollege/lcd_shared_flag.bin','build/output/imageList_NewCollege/lcd_shared_probability.bin','data/truthNewCollege.mat');