Shape-based eye blinking detection and analysis

Abstract

Methods for automated eye blinking analysis can be applied to support people with certain disabilities in interaction with technical systems, to analyse human deceptive behaviour, in driver fatigue assessment, etc. In this paper we introduce a robust shape-based algorithm for automatic eye blinking detection in video sequences. First, all video frames are classified separately into those showing an open and those corresponding to a closed eye. Second, these classification results are cleverly combined for blinking detection so that the influence of single misclassified frames gets compensated almost completely. In addition to that,we present our investigations on the user behaviour in terms of eye blinking frequency in two different everyday life situations. The most relevant scientific contributions of this paper are (1) the introduction of a new and robust feature extraction technique for the representation of images displaying eyes, (2) a smart fusion scheme improving the results for single-frame classification and (3) the compensation of wrong classification results for single frames providing an almost perfect eye blinking detection rate.