Automatic eye blink detection using consumer web cameras

This research aims to advance blinking detection in the context of work activity. Rather than patients having to attend a clinic, blinking videos can be acquired in a work environment, and further automatically analyzed. Therefore, this paper presents a methodology to perform the automatic detection of eye blink using consumer videos acquired with low-cost web cameras. This methodology includes the detection of the face and eyes of the recorded person, and then it analyzes the low-level features of the eye region to create a quantitative vector. Finally, this vector is classified into one of the two categories considered —open and closed eyes— by using machine learning algorithms. The effectiveness of the proposed methodology was demonstrated since it provides unbiased results with classification errors under 5%

This research has been partially funded by the Secretaría de Estado de Investigación of the Spanish Government and FEDER funds of the European Union through the research project PI14/02161, and by the Consellería de Cultura, Educacíon e Ordenacíon Universitaria of the Xunta de Galicia through the research project GPC2013/065. Beatriz Remeseiro acknowledges the support of the European Grouping for Territorial Cooperation Galicia-Norte de Portugal under the IACOBUS Program.