Car Safe Driving In The Human Eye Sight Estimate

The enhancement of automobile driving security depends on the research of automobile passive security and the initiative security technology. As one of initiative security technologies, it is essential to monitor the condition of the driver. In this thesis, we focus on how to estimate the gaze of human eye and detect whether the driver is sleepy in real-time with a common camera, so that we can determine whether the driver is at unsafe driving condition.First of all, we discuss the eye model. Based on the traditional spindly eye model, we ignore the down-eyelid, only retain upper-eyelid, iris and eye corners.Then, we research methods of eye features detection, including eye window positioning, eye corners detection, iris detection and eye-lid detection. And we adopt a simple method to estimate gaze. We fit the iris to a circle and regard the upper-eyelid as a section of circular arc. Then we use the method of sub-pixel detection to detect sub-pixel edge and the method of Hough transform based on gradient orientation and gradient direction to detect circle. The experiment indicates that these methods have the higher estimating precision and more timeliness under the low resolution image condition.Finally, we apply the gaze estimation algorithm this paper proposed in a real-time gaze safety examination system. This system can carry on the monitoring of the gaze direction and the sleepy condition real-time. From the running effect of this system, the efficiency of this system is very high in the laboratory environment.