humolire
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HuMoLiRe is a Pedestrian Dead-Reckoning Particle Filter Map-aided system that leverages human motion likelihood in indoor spaces to estimate their position. This repository is the dataset and software...
HuMoLiRe
Example of trajectory
Citation
This dataset and software are related to the following publication in the IEEE Sensors journal. Please cite using the following:
@ARTICLE{ghaouihumolire,
author={Ghaoui, Mohamed Anis and Vincke, Bastien and Reynaud, Roger},
journal={IEEE Sensors Journal},
title={Human Motion Likelihood Representation Map-Aided PDR Particle Filter},
year={2023},
volume={23},
number={1},
pages={484-494},
doi={10.1109/JSEN.2022.3222639}}
Introduction
This program runs on python3.8+. It is recommanded to use PyCharm.
(it can easily be turned into older version by editing every print(f"{variable=})"
call)
Entry point is main.py
. generate_figures.py
is used to recreate the figures mentionned in the article.
Requirements
requirements.txt lists:
- numpy~=1.21
- matplotlib~=3.3.3
- scipy~=1.5.4
- AHRS~=0.3.0
- imageio~=2.9.0
- tqdm~=4.51.0
- opencv-python~=4.5.1.48
Optional:
- adjustText~=0.7.3 , is used to place the purple numbers automatically
- requests~=2.22.0 , is used to send an SMS when the program is finished
Folder structure:
.
├── data
├── docs
├── humolire
├── map_editor
├── README.md
├── requirements.txt
└── tests
Documentation:
There are many README.MD files in the folders about. The main entry point is main.py. There is a beginning of documentation at read the docs. I don't have much time. If you want to help in documentation, I would be immensely grateful.
Contribution:
- If you have a research question, please reach me by email: [email protected]
- If you have a question about the code, open an issue
- If you wanna help documenting (I lack the time and skills to do that correctly), open an issue. Thank you!
LICENSE
Humolire Dataset and Software by Anis GHAOUI is licensed under a Creative Commons Attribution 4.0 International License.