Project Description:

The increasing ubiquity and capability of wireless signals (e.g., WiFi, Ultrasound, Millimeter-Wave) has extended their role of communication tool to a contactless sensing platform, as wireless signals are oftentimes affected by surrounding objects during transmission, and thus carry the information that can characterize the objects. Such contactless sensing ability gives wireless signals the potential of enabling a wide spectrum of applications, especially those related to human perception, such as smart home, gesture control, health care, elderly monitoring, and virtual/augmented reality. Wireless human sensing technique can overcome many challenges faced by traditional camera-based human perception solutions, such as clothing, background, lighting and occlusion, as well as privacy issues, so it can enable a new generation of applications by supporting more sophisticated interactions between humans and their physical surroundings. In this project, we aim to develop novel deep-learning based wireless human perception systems that can not only recognize humans' activities but also reconstruct their postures, and study the practicality of the proposed systems in real-world human-machine-environment interaction scenarios.

Start Date:

January 2023

Postdoc Qualifications:

The candidates need to be knowledgeable in interdisciplinary areas including wireless communication and networking, deep learning, and computer vision.

Co-Advisors:

Jing Gao, School of Electrical and Computer Engineering, Purdue University, Email: jinggao@purdue.edu, Web: https://engineering.purdue.edu/~jinggao/

Pan Li, Department of Computer Science, Purdue University, Email: panli@purdue.edu, Web: https://sites.google.com/view/panli-purdue/home?authuser=0&_ga=2.176214501.1575104408.1657073381-179728916.1653283294

Outside Collaborators:

Lu Su, School of Electrical and Computer Engineering, Purdue University, Email: lusu@purdue.edu, Web: https://engineering.purdue.edu/~lusu/

Bibliography:

[1] See Through Walls with Wi-Fi!, Fadel Adib and Dina Katabi, ACM Special Interest Group on Data Communication, SIGCOMM, 2013

[2] E-eyes: Device-free Location-oriented Activity Identification Using Fine-grained WiFi Signatures, Yan Wang, Jian Liu, Yingying Chen, Marco Gruteser, Jie Yang, Hongbo Liu, Proceedings of the 20th Annual International Conference on Mobile Computing and Networking

[3] Through-Wall Human Pose Estimation Using Radio Signals, Mingmin Zhao, Tianhong Li, Mohammad Abu Alsheikh, Yonglong Tian, Hang Zhao, Antonio Torralba, Dina Katabi, Conference on Computer Vision and Pattern Recognition (CVPR), 2018

[4] Wenjun Jiang, Hongfei Xue, Chenglin Miao, Shiyang Wang, Sen Lin, Chong Tian, Srinivasan Murali, Haochen Hu, Zhi Sun, Lu Su, "Towards 3D Human Pose Construction Using WiFi," the 26th ACM International Conference on Mobile Computing and Networking (MobiCom 2020), London, UK, September 2020.

[5] Hongfei Xue, Yan Ju, Chenglin Miao, Yijiang Wang, Shiyang Wang, Aidong Zhang, Lu Su, "mmMesh: Towards 3D Real-Time Dynamic Human Mesh Construction Using Millimeter-Wave," the 19th ACM International Conference on Mobile Systems, Applications, and Services (MobiSys 2021), Virtual Conference, June 2021.