New Directions in Traffic Control Analysis through Video Surveillance

Abstract

Traffic management is an increasing problem in both cities and sub urban areas. Authority people involved in traffic management system spend much of time in controlling traffic at junctions. With the advances in technology, monitoring traffic through image processing and video surveillance techniques became the researchers’ attention. These techniques help us in controlling traffic as well as to identification of kamikaze drivers and speed violators. The key focus of this research is to do traffic analysis using video surveillance to detect speedy drivers. A wide range of traffic parameters such as flow of traffic, speed of vehicles and vehicle registration number are the major components involved in this research. In this paper, traffic analysis is carried out based on streaming video data with YOLO tool. In this paper an eco system is developed for object detection, vehicle number detection and the speed of the vehicle using computer vision algorithms. With the application tool developed, traffic control authority people can warn the speedy drivers on the fly.

Keywords

• yolo tool
• object detection
• video streaming
• classification
• alpr