Image Compensation for Improving Extraction of Driver's Facial Features

Extracting driver's facial feature helps to identify the vigilance level of a driver. Some research about facial feature extraction also has been developed for controlled interface of vehicle. To acquire facial feature of drivers, research using various visual sensors have been reported. However, potential challenges to such a work include rapid illumination variation resulting from ambient lights, abrupt lighting change (e.g., entering/exiting tunnels and sunshine/shadow), and partial occlusion. In this paper, we propose an image compensation method for improve extraction of a driver's facial features. This method has the advantages of fast processing and high adaptation. Our experiments show that the extraction of driver's facial features can be improved significantly.