Development of a Real-Time Automatic Passenger Counting System using Head Detection Based onDeep Learning


Hyunduk Kim, Myoung-Kyu Sohn, Sang-Heon Lee, Journal of Information Processing Systems Vol. 18, No. 3, pp. 428-442, Jun. 2022  

10.3745/JIPS.04.0246
Keywords: Automatic Passenger Counting, Deep Learning, Embedded System, Head Detection
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Abstract

A reliable automatic passenger counting (APC) system is a key point in transportation related to the efficient scheduling and management of transport routes. In this study, we introduce a lightweight head detection network using deep learning applicable to an embedded system. Currently, object detection algorithms using deep learning have been found to be successful. However, these algorithms essentially need a graphics processing unit (GPU) to make them performable in real-time. So, we modify a Tiny-YOLOv3 network using certain techniques to speed up the proposed network and to make it more accurate in a non-GPU environment. Finally, we introduce an APC system, which is performable in real-time on embedded systems, using the proposed head detection algorithm. We implement and test the proposed APC system on a Samsung ARTIK 710 board. The experimental results on three public head datasets reflect the detection accuracy and efficiency of the proposed head detection network against Tiny-YOLOv3. Moreover, to test the proposed APC system, we measured the accuracy and recognition speed by repeating 50 instances of entering and 50 instances of exiting. These experimental results showed 99% accuracy and a 0.041-second recognition speed despite the fact that only the CPU was used.


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Cite this article
[APA Style]
Hyunduk Kim, Myoung-Kyu Sohn, & Sang-Heon Lee (2022). Development of a Real-Time Automatic Passenger Counting System using Head Detection Based onDeep Learning. Journal of Information Processing Systems, 18(3), 428-442. DOI: 10.3745/JIPS.04.0246.

[IEEE Style]
H. Kim, M. Sohn and S. Lee, "Development of a Real-Time Automatic Passenger Counting System using Head Detection Based onDeep Learning," Journal of Information Processing Systems, vol. 18, no. 3, pp. 428-442, 2022. DOI: 10.3745/JIPS.04.0246.

[ACM Style]
Hyunduk Kim, Myoung-Kyu Sohn, and Sang-Heon Lee. 2022. Development of a Real-Time Automatic Passenger Counting System using Head Detection Based onDeep Learning. Journal of Information Processing Systems, 18, 3, (2022), 428-442. DOI: 10.3745/JIPS.04.0246.