论文标题
根据碰撞估计检测道路交通崩溃
Detection of road traffic crashes based on collision estimation
论文作者
论文摘要
本文介绍了一个基于计算机视觉的框架，该框架可以通过使用已安装的监视/CCTV摄像机来检测道路交通崩溃（RCT），并实时将其报告给紧急情况，并确切的事故发生的确切位置和时间。该框架由五个模块构建。我们从使用Yolo架构对车辆的检测开始。第二个模块是使用MOSSE跟踪器对车辆进行跟踪，然后第三个模块是一种基于碰撞估计的新方法来检测事故。然后是每辆车的第四个模块，我们检测到是否存在基于暴力流动描述符（VIF）的车祸，然后是SVM分类器进行撞车预测。最后，在最后阶段，如果发生车祸，该系统将使用GPS模块向我们发送通知，该模块为我们提供了在GSM模块的帮助下向我们提供的位置，时间和日期。主要目的是通过更少的错误警报实现更高的精度，并基于管道技术实现一个简单的系统。
This paper introduces a framework based on computer vision that can detect road traffic crashes (RCTs) by using the installed surveillance/CCTV camera and report them to the emergency in real-time with the exact location and time of occurrence of the accident. The framework is built of five modules. We start with the detection of vehicles by using YOLO architecture; The second module is the tracking of vehicles using MOSSE tracker, Then the third module is a new approach to detect accidents based on collision estimation. Then the fourth module for each vehicle, we detect if there is a car accident or not based on the violent flow descriptor (ViF) followed by an SVM classifier for crash prediction. Finally, in the last stage, if there is a car accident, the system will send a notification to the emergency by using a GPS module that provides us with the location, time, and date of the accident to be sent to the emergency with the help of the GSM module. The main objective is to achieve higher accuracy with fewer false alarms and to implement a simple system based on pipelining technique.
