Abstract: The driver’s rearview mirror watching behavior is one of the necessary steps for driving
safety when the vehicle is turning, however, the detection technology or application of this behavior
is still absent. Thus an adaptive detection method of the drivers’ rearview mirror watching behaviors
during the vehicle steering process was presented in this paper with the help of vehicle vision and
image process technology for safety monitoring and reminding. A frame spatial gradient differences
searching algorithm was designed to complete the initial parameters’ learning work on both the
drivers’ face and neck regions when the vehicle engine was fired, while a expand-contract searching
algorithm was invented to accomplish a fast recognition when the vehicle was moving. Contours of
the driver's face and neck parts were extracted without segmentation. An area ration between left and
right parts of the contours separated by a vertical line passing through the base point of neck contour
was defined as a characteristic parameter. By analyzing the drivers’ eye movement data during driving, a discipline called local peak value distributing of the parameter’s cumulative probability was
uncovered, which helped to build a real time eigenvalue reference estimation method and a threshold
judging principle of the drivers’ rearview mirror watching behaviors. Experimental results showed
that this method was not sensitive to the types and details of drivers' faces, and was robust to some
disturbance, and the overall detection accuracy rate was 96.1%.

Key words: traffic safety, vehicle vision, driver, outer contour of face and neck, rearview mirror
watching behavior