A method for detecting street parking using dashboard camera videos on an edge device: demo abstract
Authors: 
Akihiro Matsuda, Tomokazu Matsui, 
Yuki Matsuda, Hirohiko Suwa, Keiichi YasumotoAuthors Info & Claims
Pages 585 - 586
Abstract
Street parking in prohibited areas has become a social problem, especially in urban and tourist areas. In addition, because street parking can cause traffic congestion and accidents, real-time detection is required. The detection of street parking has been previously implemented on the basis of comparisons of videos recorded by fixed-point cameras. However, this approach has a limited detection area and low accuracy. In this demonstration, we present a system that recognizes street parking in real-time using a model trained by dashboard camera videos, which are widely used. The trained model was constructed by collecting data on 1,765 vehicles from dashboard camera videos. We use the Jetson TX2 as an edge device for vehicle recognition and processing. We create and demonstrate a dashboard camera device by attaching a camera and sensor module to the Jetson TX2.
References
[1]
Japan Parking Association. 2019. Current Situation of Parking Measures, https://www.npa.go.jp/bureau/traffic/seibi2/kisei/tyuusya/parking.pdf.
[2]
Edgar A Bernal, Zhigang Fan, Yao Rong Wang, Robert P Loce, Norman W Zeck, and Graham S Pennington. 2013. Video-based detector and notifier for short-term parking violation enforcement. (Oct. 10 2013). US Patent App. 13/441,294.
[3]
Wen Xiao, Bruno Vallet, Konrad Schindler, and Nicolas Paparoditis. 2016. Street-side vehicle detection, classification and change detection using mobile laser scanning data. ISPRS Journal of Photogrammetry and Remote Sensing 114 (2016), 166--178.
[4]
Xuemei Xie, Chenye Wang, Shu Chen, Guangming Shi, and Zhifu Zhao. 2017. Real-time illegal parking detection system based on deep learning. In Proceedings of the 2017 International Conference on Deep learning Technologies. 23--27.
Index Terms
- A method for detecting street parking using dashboard camera videos on an edge device: demo abstract
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Information
Published In
November 2020
852 pages
ISBN:9781450375900
DOI:10.1145/3384419
Copyright © 2020 ACM.
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Association for Computing Machinery
New York, NY, United States
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Published: 16 November 2020
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- Short-paper
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SenSys '20: The 18th ACM Conference on Embedded Networked Sensor Systems
November 16 - 19, 2020
Virtual Event, Japan
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Overall Acceptance Rate 174 of 867 submissions, 20%
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