This paper presents a system which constantly monitors the level of attention of a driver in traffic. The vehicle is instrumented and can identify the state of traffic-lights, as well as obstacles on the road. If the driver is inattentive and fails to recognize a threat, the assistance system produces a warning. Therefore, the system helps the driver to focus on crucial traffic situations. Our system consists of three components: computer vision detection of traffic-lights and other traffic participants, an eye tracking device used also for head localization, and finally, a human machine interface consisting of a head-up display and an acoustic module used to provide warnings to the driver. The orientation of the driver's head is detected using fiducial markers visible in video frames. We describe how the system was integrated using an autonomous car as experimental ADAS platform.

This paper presents a method for creating a low cost stereo vision system which fits perfectly to the needs of cheap mobile robots. As mass-produced low cost CMOS cameras have no direct means for taking synchronized images, we present a method for taking synchronous images with these devices by manipulating their system clock. We also show a method of merging the data of two or more cameras for interfacing all of them to a single camera controller.