Abstract
Pedestrian counting has attracted much interest of the academic and industry communities for its widespread application in many real-world scenarios. While many recent studies have focused on computer vision-based solutions for the problem, the deployment of cameras brings up concerns about privacy invasion. This paper proposes a novel indoor pedestrian counting approach, based on footstep-induced structural vibration signals with piezoelectric sensors. The approach is privacy-protecting because no audio or video data is acquired. Our approach analyzes the space-differential features from the vibration signals caused by pedestrian footsteps and outputs the number of pedestrians. The proposed approach supports multiple pedestrians walking together with signal mixture. Moreover, it makes no requirement about the number of groups of walking people in the detection area. The experimental results show that the averaged F1-score of our approach is over 0.98, which is better than the vibration signal-based state-of-the-art methods.
Highlights
Detecting the number of people in a specific area is of great importance in many realworld scenarios
We propose a novel approach that can count the number of people with vibration signals from the piezoelectric sensors while protecting privacy
Experimental evaluation shows that our approach outperforms the vibration signal based state-of-the-art methods in accuracy for similar pedestrian counting task
Summary
Detecting the number of people in a specific area is of great importance in many realworld scenarios. The infrastructure-based approaches [5,6,7,8,9,10,11,12,13,14,15,16] deploy sensors such as cameras, infrared sensors, and piezoelectric sensors where no requirement to carry any devices is needed. The camera or infrared sensor-based approach will not work well in an extreme environment, such as areas with heavy smoke or low visibility This greatly limits the deployment of the approach in certain real-life situations, such as rescue after disasters and security monitoring in a restricted area. We propose a novel approach that can count the number of people with vibration signals from the piezoelectric sensors while protecting privacy.
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