A system for detecting and evaluating drivers gaze behavior was proposed. A system for recognizing the drivers unsafe gaze behavior was established using multi-level information and fusion decision method as well. The driving environment and condition is complex as well as the gaze behavior characteristics, and given that, a solution consists of patten classification and the multi-information decision-level fusion were put forward to estimate the different kind model of the driver's gaze behavior. In order to test the proposed strategies,the real time driver's gaze behavior detection system was established. The T characteristic curve proposed through the abnormal behavior parameters of the transverse width between the eyes and the vertical distance between mouth and the midpoint of two eyes, combined with the driver's eyelid closure and the proportion and location characteristics of iris - sclera were studied to get the characterization of the drivers gaze status information. The simulation results indicate that the adaptability and accuracy as well as the intelligent level is significantly improved by using the pattern classification and decision-making technology through multi-source information fusion.
Real-time Abnormal Behavior Detection System based on Fast Data
