Grayscale Correlation based 3D Model Fitting for Occupant Head Detection and Tracking

Abstract

Occupants inside the vehicle can be deadly injured by the deployment of airbag at the time of crash. New collision safety technology requires classifying the occupant and tracking their position in real-time in order to adaptively deploy the air bag. This paper presents a fast 3D model fitting algorithm based on grayscale correlation of stereo disparity data, to detect and track occupant head position. The proposed system uses stereo vision with IR illumination for depth data acquisition. By detecting body center line and extra-near disparity calculation, this method is proven to be robust and accurate in variant lighting condition and occupant movement. Evaluation of the method shows over 98% correct head detection and near 100% correctness with head tracking.