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Intrusion Detection and Tracking at Railway Crossing

Published: 17 October 2019 Publication History

Abstract

Railway crossing safety is an issue of great public concern. With the development of computer vision, intelligent video surveillance was widely used for object detection. However, most existing object detection methods could not perform well in outdoor environment, especially under the bad weather conditions. In this paper, an intrusion detecting algorithm was proposed for railway crossing. Our method consists of the following three steps. First, three nonparametric background models with different learning rates are designed for the detection of moving and static objects. Second, an object tracking strategy is introduced for reducing false positives in the detection. Finally, a feedback mechanism is introduced to selectively update the background models when static objects are removed. Our method was tested on real railway sequences and the public i-LIDS datasets. Experimental results showed the proposed method achieves accurate detection for both moving and static objects and some false positives caused by rains and partial occlusion could be reduced.

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Cited By

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  • (2024)A Railway Similarity Multiple Object Tracking Framework Based on Vehicle Front VideoProceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 202310.1007/978-981-99-9319-2_9(73-81)Online publication date: 4-Jan-2024
  • (2023)Railroad Crossing Surveillance and Foreground Extraction Network: Weakly Supervised Artificial-Intelligence ApproachTransportation Research Record: Journal of the Transportation Research Board10.1177/036119812311594062677:9(525-538)Online publication date: 28-Mar-2023
  • (2023)A Review of Intelligent Infrastructure Surveillance to Support Safe Autonomy in Smart-Railways2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC57777.2023.10422317(5603-5610)Online publication date: 24-Sep-2023
  • Show More Cited By

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Published In

cover image ACM Other conferences
AIAM 2019: Proceedings of the 2019 International Conference on Artificial Intelligence and Advanced Manufacturing
October 2019
418 pages
ISBN:9781450372022
DOI:10.1145/3358331
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 17 October 2019

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Author Tags

  1. moving and static objects
  2. object detection
  3. railway crossing

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  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • National Natural Science Foundation of China

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AIAM 2019

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Overall Acceptance Rate 100 of 285 submissions, 35%

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Cited By

View all
  • (2024)A Railway Similarity Multiple Object Tracking Framework Based on Vehicle Front VideoProceedings of the 6th International Conference on Electrical Engineering and Information Technologies for Rail Transportation (EITRT) 202310.1007/978-981-99-9319-2_9(73-81)Online publication date: 4-Jan-2024
  • (2023)Railroad Crossing Surveillance and Foreground Extraction Network: Weakly Supervised Artificial-Intelligence ApproachTransportation Research Record: Journal of the Transportation Research Board10.1177/036119812311594062677:9(525-538)Online publication date: 28-Mar-2023
  • (2023)A Review of Intelligent Infrastructure Surveillance to Support Safe Autonomy in Smart-Railways2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)10.1109/ITSC57777.2023.10422317(5603-5610)Online publication date: 24-Sep-2023
  • (2022)Aerial Footage Analysis Using Computer Vision for Efficient Detection of Points of Interest Near Railway TracksAerospace10.3390/aerospace90703709:7(370)Online publication date: 9-Jul-2022
  • (2022)Analysis and Evaluation of the Effectiveness of Safety Systems at Railroad Crossings in PolandCommunications - Scientific letters of the University of Zilina10.26552/com.C.2022.3.F46-F6124:3(F46-F61)Online publication date: 1-Jul-2022
  • (2021)Live Stream Processing Techniques to Assist Unmanned, Regulated Railway CrossingsAdvances in Computing and Data Sciences10.1007/978-3-030-81462-5_17(181-192)Online publication date: 23-Oct-2021
  • (2021)Towards Automated Surveillance: A Review of Intelligent Video SurveillanceIntelligent Computing10.1007/978-3-030-80129-8_53(784-803)Online publication date: 6-Jul-2021
  • (2020)Proposed Methodology for the Calculation of Overview Distances at Level Crossings and the Inclusion Thereof in National StandardsSustainability10.3390/su1214568412:14(5684)Online publication date: 15-Jul-2020
  • (2020)A Deep Learning Approach Towards Railway Safety Risk AssessmentIEEE Access10.1109/ACCESS.2020.29979468(102811-102832)Online publication date: 2020

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