Evaluation of Stereo Matching Algorithms for Occupant Detection

Vision systems within vehicles offer new opportunities in the automobile industry. The detection and classification of passenger and driver seat occupancy open up new ways to improve the safety and comfort of the passengers. In this paper we present results of a stereo system designed for the observation of the cockpit scene in order to provide information about the passenger presence and location within the vehicle to improve the control of the airbag firing. We compare different techniques and examine the effect of random and systematic errors on the performance in precision, robustness and processing speed. These results establish a foundation for on-going work on occupant detection for vehicle safety.