Safe Driving : Driver Action Recognition using SURF Keypoints

Abstract

Driver distraction is one of the main factors of fatal road traffic injuries. According to the national Highway Traffic Safety Administration (NHTSA), in USA, 3450 are killed by distracted driving, in 2016. In order to save lives, Advanced Driver Assistance Systems (ADAS), more specifically those systems for distracted driver action recognition are introduced. Our method aim to extract, from each frame, a region of interest (KOI) that contains body parts performing in-vehicle actions. These regions hold the most important key points after eliminating those common ones that are similar to the key points of the safe driving actions. The proposed approach was evaluated on the distracted driver detection dataset. Experimental results illustrate the performance of the proposed approach.