Yawn analysis with mouth occlusion detection. (April 2015)

• Record Type: Journal Article
• Authors: Ibrahim, Masrullizam Mat; Soraghan, John J.; Petropoulakis, Lykourgos; Di Caterina, Gaetano
• Is Part Of: Biomedical signal processing and control. Volume 18(2015)
• Page Start: 360
• Page End: 369
• Publication Date: 2015-04
• Subjects: Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2015.02.006
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: Yawning is detected upon mouth opening, mouth covering and facial feature distortion. Mouth covered detection is based on classification of LBP features extracted from mouth covering hand. Proposed approach has been tested on real video sequences of sleep deprived volunteers. Abstract: One of the most common signs of tiredness or fatigue is yawning. Naturally, identification of fatigued individuals would be helped if yawning is detected. Existing techniques for yawn detection are centred on measuring the mouth opening. This approach, however, may fail if the mouth is occluded by the hand, as it is frequently the case. The work presented in this paper focuses on a technique to detect yawning whilst also allowing for cases of occlusion . For measuring the mouth opening, a new technique which applies adaptive colour region is introduced. For detecting yawning whilst the mouth is occluded, local binary pattern (LBP) features are used to also identify facial distortions during yawning. In this research, the Strathclyde Facial Fatigue (SFF) database which contains genuine video footage of fatigued individuals is used for training, testing and evaluation of the system.