SFDEFRSS: Single Frmae Depth Estimation for Rolling Shutter Stereo
Citation
@ARTICLE{9369005,
author={Wang, Ke and Liu, Chuhao and Wang, Kaixuan and Shen, Shaojie},
journal={IEEE Robotics and Automation Letters},
title={Depth Estimation Under Motion With Single Pair Rolling Shutter Stereo Images},
year={2021},
volume={6},
number={2},
pages={3160-3167},
doi={10.1109/LRA.2021.3063695}}
1. Installation
git clone https://github.com/kewangtt/SFDEFRSS.git
1.1 Required Dependencies
suitesparse and eigen3 (required). Install with
sudo apt-get install libsuitesparse-dev libeigen3-dev libboost-all-dev
OpenCV (>=3.4) and CUDA
1.2 Build
cd SFDEFRSS
mkdir build
cd build
cmake ..
make
this will compile an executable file SFRSS_EXE
in the build directory.
2. Usage
2.1 Create sub-discretionary
sh create_subdir.sh
2.2 Run
Run an example sequence by
./build/SFRSS_EXE ./example 0
this will generate all results of the example sequence. The computed results are saved in
./Result/disparity_rgb "rgb disparity for visualization"
./Result/undited_depth "undistorted depth map"
./Result/motion_states "estimated motion states (a_x, a_y, a_z, v_x, v_y, v_z)"
./Result/baseline_map "baseline map"
a_x, a_y, a_z
and v_x, v_y, v_z
are the estimated angular speed and velocity respectively.
The depth map is saved as a binary file and data type is double type. Thus, the size of depth map is
sizeof(double)*height*width.
All external parameters and calibration parameters are saved in
./example/SFRSS.yaml
.
We also provide the close-form motion state solver proposed in "From two rolling shutters to one global shutter". Which can be run by
./build/SFRSS_EXE ./example 1
We save the 20 candidates solutions with the most inliers in .\example\Result\close_form
.
3. Demo video
4. License
The open-source version is licensed under the GNU General Public License Version 3 (GPLv3).