Car crash detection in videos
Veronica Radu, Mihai Nan, Mihai Trăşcău, David-Traian Iancu, Alexandra Ștefania Ghiță, Adina Magda Florea · 2021
Increasing the number of cars and excessive traffic congestion in cities is a major problem in the current time. Statistics show that more and more accidents happen daily, and many of these could be avoided. This article aims to develop a system capable of detecting the possibility of an accident by analyzing a video sequence. In this sense, this paper presents a dataset built on those available on the Internet and a series of video classification models. Based on the experimental results obtained, we show what are the main vulnerabilities of each model. The main contribution is that we tried different architectures on a dataset that contains videos from a first-person perspective of the camera, being more challenging to generalize this behavior, but more useful for the autonomous driving systems.