Seatbelt detection based on cascade Adaboost classifier

Abstract

Vehicle safety is increasingly becoming a concern. Whether the driver is wearing a seatbelt and whether the vehicle is speeding out or not become important indicators of the vehicle safety. However, manually searching, detecting, recording and other work will spend a lot of manpower and time inefficiently. This paper proposes a cascade Adaboost classifier based seatbelt detection system to detect the vehicle windows, to complete Canny edge detection on gradient map of vehicle window images, and to perform the probabilistic Hough transform to extract the straight-lines of seatbelts. The system achieves the goal of seatbelt detection intelligently.