Yawn analysis with mouth occlusion detection

tOne of the most common signs of tiredness or fatigue is yawning. Naturally, identification of fatiguedindividuals would be helped if yawning is detected. Existing techniques for yawn detection are centred onmeasuring the mouth opening. This approach, however, may fail if the mouth is occluded by the hand, as itis frequently the case. The work presented in this paper focuses on a technique to detect yawning whilstalso allowing for cases of occlusion. For measuring the mouth opening, a new technique which appliesadaptive colour region is introduced. For detecting yawning whilst the mouth is occluded, local binarypattern (LBP) features are used to also identify facial distortions during yawning. In this research, theStrathclyde Facial Fatigue (SFF) database which contains genuine video footage of fatigued individuals isused for training, testing and evaluation of the system

Sitting behaviour-based pattern recognition for predicting driver fatigue

The proposed approach based on physiological characteristics of sitting behaviours and sophisticated machine learning techniques would enable an effective and practical solution to driver fatigue prognosis since it is insensitive to the illumination of driving environment, non-obtrusive to driver, without violating driver’s privacy, more acceptable by drivers