vrajur / PVIO

Robust and Efficient Visual-Inertial Odometry with Multi-plane Priors

Robust and Efficient Visual-Inertial Odometry with Multi-plane Priors
Jinyu Li, Bangbang Yang, Kai Huang, Guofeng Zhang, and Hujun Bao*
PRCV 2019, LNCS 11859, pp. 283–295, 2019.

How to use

For compilation:

• Install the dependencies: Eigen, Ceres Solver and OpenCV.
• Clone the repository.
• Build with mkdir -p build && cd build && cmake -DCMAKE_BUILD_TYPE=Release .. && make -j8, you will need a compiler supporting C++17.
• Tested in Ubuntu 18.04 (with GCC 9.0 and CMake 3.11), and macOS 10.14.

For execution:

• ./pvio-pc -t=[data_scheme] -d=[data_path] -c=[config_yaml_path]
• Optional args are:
  • -m for the mode which is one of:
    • default: run the full visualization system and log the output trajectory
    • headless: run PVIO without the visualization and just generate the output trajectory. The default value is default.
  • -o for specifying the path for the output file. The default value is trajectory.tum
  • -h which displays information about the supported commandline arguments
  • e.g.
    • For EuRoC Dataset: build/pvio-pc/pvio-pc -t=euroc -d=/Data/EuRoC/V1_01_easy/mav0 -cconfig/euroc.yaml
    • For TUM-VI Dataset: build/pvio-pc/pvio-pc -t=tumvi -d=/Data/TUM_VI/dataset-room1_512_16/mav0 -c=config/tum_vi.yaml

Publication

If you use this source code for your academic publication, please cite the following paper.

@inproceedings{PRCV-LiYHZB2019,
  author={Jinyu Li and Bangbang Yang and Kai Huang and Guofeng Zhang and Hujun Bao},
  title     = {Robust and Efficient Visual-Inertial Odometry with Multi-plane Priors},
  booktitle = {Pattern Recognition and Computer Vision - Second Chinese Conference,
               {PRCV} 2019, Xi'an, China, November 8-11, 2019, Proceedings, Part {III}},
  series    = {Lecture Notes in Computer Science},
  volume    = {11859},
  pages     = {283--295},
  publisher = {Springer},
  year      = {2019}
}

Acknowledgements

This work is affliated with ZJU-SenseTime Joint Lab of 3D Vision, and its intellectual property belongs to SenseTime Group Ltd.

Copyright

Copyright (c) ZJU-SenseTime Joint Lab of 3D Vision. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.