Automatic Accident Detection Techniques using CCTV Surveillance Videos: Methods, Data sets and Learning Strategies

Author:

Jahagirdar Shilpa, ,Koli Sanjay,

Abstract

Intelligent communities are utilizing different creative ideas to improve the quality of human life. Due to fast growing sizes of our cities, need of travelling is constantly increasing, which in turn has increased count of vehicles on the roads. Increasing number of vehicles on the roads has brought about numerous difficulties for Street Traffic Management Authorities. Amongst different traffic related issues, road accidents are something worth giving attention to and have to be on the priority list. This paper describes various automatic road accident detection techniques, which automatically detect accidents using surveillance videos in real-time. As these methods do not consider various lighting conditions, changing weather conditions and different traffic patterns, none of the methods are robust enough to address all the incidences of the accident. In this paper, authors have described and compared many such methods.

Publisher

Blue Eyes Intelligence Engineering and Sciences Engineering and Sciences Publication - BEIESP

Subject

Computer Science Applications,General Engineering,Environmental Engineering

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Continuous Trajectory Tracking Across Sensors at Intersection using Dynamic Target Set within the Overlapping Area;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24

2. Accident Prone System using YOLO;International Journal of Scientific Research in Science, Engineering and Technology;2023-04-20

3. Real Time Gesture Detection Using Convolutional Neural Network;2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA);2022-10-08

4. Single Shot Detector for Multi-vehicle Detection and Tracking in Different Lighting and Weather Conditions;Lecture Notes in Electrical Engineering;2022

5. Accident Detection System Using Deep Learning;IFIP Advances in Information and Communication Technology;2022

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