Project for MILD: An efficient loop closure detection libary based on binary features.
Multi-Index Hashing for Loop closure Detection. International Conference on Multimedia Expo, 2017. Best Student Paper Awards.
Beyond SIFT Using Binary features in Loop Closure Detection. IROS 2017.
OpenCV 3.1 http://xfloyd.net/blog/?p=987
octave (optional, only used for evaluation)
$ mkdir build
$ cd build
$ cmake ..
./mild imagelist.txt settings.yaml
imageList.txt: indicats the path of each input RGB image per line settings.yaml: indicats the parameters used in loop closure detection
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)