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With the increase in number of vehicles in the country vehicle detection is an important in road traffic management system. Different traffic accident causes such as vehicle overspeeding, wrong way driving, collision and accident can be detected by CCTV installed on roads. The results obtained from traffic parameters can be applied for vehicle tracking, vehicle classification, parking area monitoring, road traffic monitoring and management etc. The main objective of this project is to decrease the deaths caused by accident occurring because over speeding, wrong war driving by ensuring public safety and also a building a better system for managing the traffic on the roads. The aim of this paper is to develop a system that can detect the vehicle accident which are caused by overspeeding, wrong way driving and collision detection on city roads. A prototype system is developed and tested. deep learning, heatmap, openCV, ROI, SSD model, tensor flow.
Shrey Gupta, Vandana Choudhary. 2019. "Accident Detection in Live Surveillance". Global Journal of Computer Science and Technology - H: Information & Technology GJCST-H Volume 19 (GJCST Volume 19 Issue H1).
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
v1.2
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Total Score: 142
Country: India
Subject: Global Journal of Computer Science and Technology
Authors: Shrey Gupta, Vandana Choudhary (PhD/Dr. count: 0)
View Count (all-time): 321
Total Views (Real + Logic): 2273
Total Downloads (simulated): 161
Publish Date: 2019 01, Tue
Monthly Totals (Real + Logic):
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