Dynamic Bird’s Eye View Reconstruction of Driving Accidents

The consequences of vehicle crashes are extremely costly, especially in industrial contexts, where the loss of income due to the vehicle unavailability while the incident is investigated adds to the damage produced by the event. The ongoing shift toward more connected vehicles, featuring sensors and cameras, offers the opportunity to alleviate such losses by speeding up the resolution of disputes. In this paper, we show how data routinely collected by connected vehicles can be fused to attain automatic reconstruction of the crash dynamic, a key element that has to be provided by drivers to submit a First Notification of Loss. We build upon state-of-the-art methods in areas such as SLAM, depth estimation and object detection to create a reconstruction of the scene with the vehicles involved localized both in space and time, which we present in an animated bird’s eye view. Our pipeline is evaluated on a challenging benchmark of real world videos and it is shown to create reliable reconstructions of the moment of the impact in more than 50% of scenes and overall good reconstructions in about 37% of them.