MMCOUNT: Stationary Crowd Counting System Based on Commodity Millimeter-Wave Radar

• Published in: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 56 - 60
• Main Authors: Hu, Kaiyuan, Liao, Hongjie, Li, Mingxiao, Wang, Fangxin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.04.2024
• Subjects: Crowd Counting; Data mining; Millimeter wave radar; Millimeter Wave Sensing; Motion pictures; Object detection; Occupancy Estimation; Radar tracking; Sensors; Signal processing
• DOI: 10.1109/ICASSP48485.2024.10447408

Millimeter wave sensing promises the capability of sensing the surrounding moving people. However, it is still challenging for stationary crowds because objects with few motions (like changing sitting position) are easily treated as a cluster of noise and thus neglected. In this paper, we propose that people's respiration and natural fidgeting (restless behavior) carry valuable information, which could be captured by millimeter (mmWave) radar. By performing processing on the captured data including signal enhancement and object recognition, we can successfully extract the number of a crowd and the position of each individual. To verify our system, we test it in different locations like hall, classroom, and meeting room to simulate different practical scenarios including watching a movie, having a class, or attending a meeting. The evaluation results show that our proposed approach could reach a high counting accuracy of up to 95.8% even at small separation distances of 0.4m.