An Automatic Car Accident Detection Method Based on Cooperative Vehicle Infrastructure Systems - IT Assignment Help

Assignment Task

INTRODUCTION

Motivation - With the computation capability of the modern CPU processors, many complex real-time applications have been made possible and implemented in various fields worldwide. One of the widely used real-time applications is video surveillance systems. Video surveillance systems are been used for security monitoring, anomaly detection, traffic monitoring and many other purposes. Video surveillance systems have decreased the need of human presence to monitor activities captured by video cameras. And also one of the advantages of visual surveillance systems is videos can been stored and analyzed for future reference. One of the important applications of video surveillance systems is traffic surveillance. Extensive research has been done in the field of video traffic surveillance. Video traffic surveillance systems are used for vehicle detection, tracking, traffic flow estimation, vehicle speed detection, vehicle classification, etc. Video traffic surveillance has paved for numerous applications such as ATMS (Advanced Transportation Management Systems) [1] and (ITS) Intelligent Transportation Systems.

Research Goal and Challenges

Overview Although considerable amount of research has been done to develop a system that can detect an accident through video surveillance, real-time implementation of all these systems have not been realized yet. Real-time implementation of accident detection through video-based traffic surveillance have always been challenging since one has to strike a right balance between the speed of the system and the performance of the systems such as correctly detecting accidents and also reducing false alarm rate. Ideally we want a system that could maximize the number of frames processed per second at the same time able to achieve acceptable performance rate. This brings us to the goal of this research.

The goal of this research is to develop an accident detection module at roadway intersections through video processing that is suitable for real-time implementation. In this thesis we developed an accident detection module that uses the parameters extracted from the detected and tracked vehicles which is able to achieve good realtime performance.

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