Video-based Assistance for Autonomous Driving

Abstract

Computer vision techniques implemented in modern vehicles should be designed to distinguish different changes in a video sequence, captured by RGB and RGBD cameras mounted in or out a vehicle. Autonomous driving process could improve safety of all passengers by introducing additional sensing. In this paper, we used input data from mentioned cameras acquired with inertial sensor for road roughness as a limiter of velocity. Abrupt changes of the velocity and driver comfort affects the driver’s head position. The head position is monitored using 3D skeleton model and depth information. The results show possibility of detection of the potential risk found for unusual driver behavior. Then, the human control could be taken by safety application and system.