CAR DETECTION IN LIVE SURVEILLANCE USING DEEP LEARNING
Shrey Gupta, Vandana Choudhary
Deep Learning, Heatmap, OpenCV, ROI, SSD Model, TensorFlow
With the increase in number of vehicles in the country vehicle detection is an important in road traffic management system. Different traffic parameters such as vehicle speed, count, traffic movement rate, travelling time, traffic congestion level can be calculated by using vehicle detection method. 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 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, classify and count the vehicle and detect speed of the vehicle on city roads using deep learning technology. A prototype system is developed and tested.