See THREE video demos at https://lasso-sustech.github.io/CASTER or http:https://lasso.eee.sustech.edu.cn/caster/ for a quick understanding of our efforts!
SDP3 (IOTJ) | PBAH (SPAWC) | CASTER (OJ-COMS) |
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testSpectrogram is an open-source platform for wireless channel simulation, human/hand pose extraction, gesture spectrogram generation, and real-time gesture recognition based on millimeter-wave passive sensing and communication systems.
Since this work is experiment-oriented, code might not be 100% consistent with our real implementation. But the gerneral core idea is the same. And we will keep making improvements and updating the code for clearer understanding.
git clone https://github.com/rzy0901/testSpectrogram.git --recursive
Alternatively, you can visit the repositories listed in .gitmodules and download each one individually as a zip file.
- Micro_Doppler_Radar_Simulator
- Data driven hybrid channel model simulation using a Boulic Human walking model.
- testZED and zed_pose
- Simple Mocap-based channel simulation example.
- Camera coordinate 3D human keypoints extraction based on the depth camera ZED 2i, using zed-sdk.
- mediapipe_spectrogram
- CASTER_classification and RxRealTime_GUI_rzy
- "Simulation-to-reality" hand gesture recognition based on ResNet18.
- Transfer learning based on the simulated dataset and real-world dataset.
- Real-time gesture recognition based on millimeter-wave passive sensing and communication systems, using a model trained by a simulated dataset.
@inproceedings{li2021wireless,
title={Wireless sensing with deep spectrogram network and primitive based autoregressive hybrid channel model},
author={Li, Guoliang and Wang, Shuai and Li, Jie and Wang, Rui and Peng, Xiaohui and Han, Tony Xiao},
booktitle={2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)},
pages={481--485},
year={2021},
organization={IEEE}
}
@article{li2023integrated,
title={Integrated Sensing and Communication from Learning Perspective: An SDP3 Approach},
author={Li, Guoliang and Wang, Shuai and Li, Jie and Wang, Rui and Liu, Fan and Peng, Xiaohui and Han, Tony Xiao and Xu, Chengzhong},
journal={IEEE Internet of Things Journal},
year={2023},
publisher={IEEE}
}
@ARTICLE{ren2024caster,
author={Ren, Zhenyu and Li, Guoliang and Ji, Chenqing and Yu, Chao and Wang, Shuai and Wang, Rui},
journal={IEEE Open Journal of the Communications Society},
title={CASTER: A Computer-Vision-Assisted Wireless Channel Simulator for Gesture Recognition},
year={2024},
volume={5},
number={},
pages={3185-3195},
doi={10.1109/OJCOMS.2024.3398016},
ISSN={2644-125X},
month={},}
This series of work is under supervision of Prof. Rui Wang and Prof. Shuai Wang.