Awesome
TEGBP
Official repo for CVPR 2023 Paper "Tangentially Elongated Gaussian Belief Propagation for Event-based Incremental Optical Flow Estimation" Jun, Nagata and Yusuke Sekikawa
@inproceedings{cvpr2023tegbp,
author = {Jun, Nagata, and Yusuke, Sekikawa},
title = {Tangentially Elongated Gaussian Belief Propagation for Event-based Incremental Optical Flow Estimation},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2023},
url={https://openreview.net/attachment?id=FppNuRVrS8&name=camera-ready_PDF}
}
<!-- <img src="https://github.com/DensoITLab/tegbp/blob/master/material/flo_1_00009.png" alt="normal flow" title="normal flow"> --> <!-- <img src="https://github.com/DensoITLab/tegbp/blob/master/material/flo_0_00009.png" alt="full flow" title="full flow"> -->
Setup dependency
sudo apt install libeigen3-dev
pip install Command
source /opt/intel/oneapi/setvars.sh --force
Prepare result folder
Local SSD is recomended.
ln -s /home/data2/cashe/tegbp_result/ result
sudo chmod -R 777 result
mkdir result/bricks_1slide
mkdir result/dummy
mkdir result/bricks
mkdir result/indoor_flying2
Compile
source /opt/intel/oneapi/setvars.sh
make
MakeFile options
-fexcess-precision=fast -ffast-math -mssse3 -mfpmath=sse
Run
./process #thread dataname win_size save_interval
./process =1 "indoor_flying2" -1 -1
./process -1 "bricks" 15000 // debug
./process -1 "indoor_flying2" -1 -1
Visualization
Run vis_result.ipynb
.
It'll execute the followng operations
- run the core program (cpp),
- show the optical flow,
- and saved the resutls as png file
If you can not open notebook, first convert it to the python script and then execute as a python script.
jupyter nbconvert --to script vis_result.py vis_result.ipynb
python vis_result.py
Misc
See matlab
directory for the reference matlab implementation (slow).
Credit
Coder: Y.Sekikawa, J.Nagata