I am working on trying to classify dashcam videos of car crashes as Head-on, Rear-end by others, Rear-end by us, Sideswipe, T-Bone by others and T-Bone by us. We are only bothered about the videos where the dashcam car is involved in the accident. There are two types of accidents involved here

1. Visible on dashcam footage – Head-on, Rear-end by us, etc
2. Not visible on dashcam footage – Rear-end by others, T-Bone by others

Working with motion features seemed like a good idea to classify this. I have tried using the ideas from “Action Recognition with Improved Trajectories” to build a classifier. However, this has not proved fruitful. As a solution for the visible accident subcase, I am able to identify the other car involved in the accident and pass it through an image classification algorithm to obtain satisfactory results. I am currently exploring dynamic time warping to figure out a solution.

It seems like an interesting problem to solve. Any leads on how to approach this would be highly appreciated. 🙂