• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

A study on counting number of passengers by moving object detection


Sang-Hyun Yoo, Journal of Internet Computing and Services, Vol. 21, No. 2, pp. 9-18, Apr. 2020
10.7472/jksii.2020.21.2.9, Full Text:
Keywords: Moving object detection, Object Contours Detection, Bus Passenger Counting

Abstract

In the field of image processing, a method of detecting and counting passengers as moving objects when getting on and off the bus has been studied. Among these technologies, one of the artificial intelligence techniques, the deep learning technique is used. As another method, a method of detecting an object using a stereo vision camera is also used. However, these techniques require expensive hardware equipment because of the computational complexity of used to detect objects. However, most video equipments have a significant decrease in computational processing power, and thus, in order to detect passengers on the bus, there is a need for an image processing technology suitable for various equipment using a relatively low computational technique. Therefore, in this paper, we propose a technique that can efficiently obtain the number of passengers on the bus by detecting the contour of the object through the background subtraction suitable for low-cost equipment. Experiments have shown that passengers were counted with approximately 70% accuracy on lower-end machines than those equipped with stereo vision camera.


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Cite this article
[APA Style]
Yoo, S. (2020). A study on counting number of passengers by moving object detection. Journal of Internet Computing and Services, 21(2), 9-18. DOI: 10.7472/jksii.2020.21.2.9.

[IEEE Style]
S. Yoo, "A study on counting number of passengers by moving object detection," Journal of Internet Computing and Services, vol. 21, no. 2, pp. 9-18, 2020. DOI: 10.7472/jksii.2020.21.2.9.

[ACM Style]
Sang-Hyun Yoo. 2020. A study on counting number of passengers by moving object detection. Journal of Internet Computing and Services, 21, 2, (2020), 9-18. DOI: 10.7472/jksii.2020.21.2.9.