Real-time vehicle back-up warning system with a single camera

In this paper, we propose a real-time system using vehicle back-up camera to alert for potential back-up collisions. We developed a highly efficient algorithm, combining segmenting pedestrians and vehicles from moving background using local optical flow value, and a scale adaptive method using Deformable Part Model to detect objects at different distances. To test out algorithm, we created our own vehicle back-up dataset that contains rich scenes recorded from a back-up camera on moving/stationary vehicles with unique and challenging scenarios such as frequent occlusion with cluttered and moving background, and we made this dataset available to public for other researchers. Experiments on the dataset shows that our algorithm achieves high accuracy in near real-time, and it is about 10 times faster than the comparable state-of-the-art algorithm.