Video Re-sampling and Content Re-targeting for Realistic Driving Incident Simulation

Abstract

We present a video generation and visualization system for integration into a driving incident simulator. We combine the use of video re-sampling, target tracking and object segmentation for content re-targeting to generate realistic video content that can be adapted on demand, based upon simulator inputs to generate a range of driver incident test scenario