Direction Estimation of Drone Collision Using Optical Flow for Forensic Investigation

Abstract

Nowadays drones have an important role to help people in several aspects. For example, drones are very beneficial in military sector. In this sector, drones may have a collision with different reasons, such as human error and a malfunctioning system. Therefore, forensic investigation helps the authority to find out drone collision cause. One indication before having collision is a change of direction of the drone. This cause can be detected by analyzing drone flying direction which changes irregularly. In this paper, we propose to use direction estimation method to assist the forensic investigation of a drone collision. We apply optical flow methods, specifically Lucas-Kanade, Horn-Schunck, and Gunnar-Farnerback. Based on the experimental results, Lucas-Kanade technique can achieve the best direction estimation providing a specific motion vector and also a filter to reduce noise.