Contact Versus Noncontact Detection of Driver's Drowsiness.

With an estimated number of injuries in the millions, accidents caused due to drowsy driving remain a significant source of financial costs and loss of life. Accurate detection of driver's drowsiness could provide a clear avenue towards eliminating a great majority of the associated accidents and losses. Existing research on the subject could be defined as either contact-based or noncontact-based alertness detection. This paper utilizes a novel multimodal driver's alertness dataset consisting of 45 subjects via seven recorded channels, including four contact-based and three noncontact-based channels, to investigate the performance of said modalities in detecting driver's drowsiness as well as provide a novel comparison between the results of multiple contact and noncontact methods. Our results highlight the viability of noncontact methods to detect driver's drowsiness as an implementable technology in automobiles.