Correlation Flow: Robust Optical Flow using Kernel Cross-Correlators
Velocity Estimation in 3-D space $v_x, v_y, v_z, \omega_z$
This repo contains source codes for the following paper, which is accepted by ICRA-18:
Chen Wang *, Tete Ji *, Thien-Minh Nguyen, and Lihua Xie, "Correlation Flow: Robust Optical Flow Using Kernel Cross-Correlators", IEEE International Conference on Robotics and Automation (ICRA), 2018.
Codes have been tested on Ubuntu 16.04 with ROS kinetic.
- Install FFT library:
sudo apt-get install libfftw3-dev libfftw3-doc
MKL is optional but highly recommended for computational efficiency. It improves the running speed a lot.
- Download MKL from Intel website
- Extract downloaded file
tar -zxvf [name_of_downloaded_file] - Go to extracted folder, give permission:
sudo chmod +x install.sh - Run installation
./install.sh - Link library, add to .bashrc:
source /opt/intel/bin/compilervars.sh intel64 - Try compile in ROS workspace
@inproceedings{wang2018correlation,
title={{Correlation Flow: Robust Optical Flow using Kernel Cross-Correlators}},
author={Wang, Chen and Ji, Tete and Nguyen, Thien-Minh and Xie, Lihua},
booktitle={International Conference on Robotics and Automation (ICRA)},
year={2018},
organization={IEEE}
}
Chen Wang, Le Zhang, Lihua Xie, Junsong Yuan, Kernel Cross-Correlator, In AAAI Conference on Artificial Intelligence (AAAI-18), 2018 (PDF available here) (source codes available here)
Thien-Minh Nguyen, Abdul Hanif Zaini, Chen Wang , Kexin Guo, and Lihua Xie, "Robust Target-relative Localization with Ultra-Wideband Ranging and Communication", IEEE International Conference on Robotics and Automation (ICRA 2018), 2018. (Video available here)
*The above work applys correlation flow to improve the performance of localization accuracy.