Many road accidents are caused by drowsiness of the driver. While there are methods to detect closed eyes, it is a non-trivial task to detect the gradual process of a driver becoming drowsy. We consider a simple real-time detection system for drowsiness merely based on the eye blinking rate derived from the eye aspect ratio. For the eye detection we use HOG and a linear SVM. If the speed of the eye blinking drops below some empirically determined threshold, the system triggers an alarm, hence preventing the driver from falling into microsleep. In this paper, we extensively evaluate the minimal requirements for the proposed system. We find that this system works well if the face is directed to the camera, but it becomes less reliable once the head is tilted significantly. The results of our evaluations provide the foundation for further developments of our drowsiness detection system.
翻译:许多道路事故都是由驾驶员昏睡造成的。 虽然有办法探测闭眼者,但发现驾驶员逐渐沉睡的过程并非一项三重任务。我们仅仅根据从眼睛侧面比率得出的眨眼率来考虑一个简单的实时沉睡探测系统。我们使用HOG和线性SVM来检测眼部。如果眼睛眨眼速度低于某种经经验确定的临界值,那么这个系统会触发警报,从而阻止驾驶员进入微型睡眠状态。在本文中,我们广泛评价了拟议系统的最低要求。我们发现,如果脸朝镜头看,这个系统的运作良好,但一旦头部明显倾斜,它就会变得不那么可靠。我们的评估结果为进一步发展我们的沉睡探测系统提供了基础。