Yawning Recognition based on Dynamic Analysis and Simple Measure

Nowadays drivers fatigue is amongst significant causes of traffic accidents. There exist many academic and industrial publications, where fatigue detection is presented. Yawning is one of the most detectable and indicative symptoms in such situation. However, yawning identification approaches which have been developed to date are limited by the fact that they detect a wide open mouth. And the detection of open mouth can also mean talking, singing and smiling, what is not always a sign of fatigue. The research aims was to investigate the different situations when the mouth is open and distinguish situation when really yawning occurred. In this paper we use an algorithm for localization of the facial landmarks and we propose a simple and effective system for yawning detection which is based on changes of mouth geometric features. The accuracy of presented method was verified using 80 videos collected from three databases: we have used 20 films of yawning expression, 30 films of smiling and 30 films with singing examples. The experimental results show high accuracy of proposed method on the level of 93%. The obtained results have been compared with the methods described in the literature – the achieved accuracy puts proposed method among the best solutions of recent years.