Human eye blinks include voluntary (conscious) blinks and involuntary (unconscious) blinks. If voluntary blinks can be detected automatically, then input decisions can be made when voluntary blinks occur. Previously, we proposed a novel eye blink detection method using a Hi-Vision video camera. This method utilizes split interlaced images of the eye, which are generated from 1080i Hi-Vision format images. The proposed method yields a time resolution that is twice as high as that of the 1080i Hi-Vision format. We refer to this approach as the frame-splitting method. In this paper, we propose a new method for automatically classifying eye blink types on the basis of specific characteristics using the frame-splitting method. © 2013 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Abe, K., Sato, H., Matsuno, S., Ohi, S., & Ohyama, M. (2013). Automatic classification of eye blink types using a frame-splitting method. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8019 LNAI, pp. 117–124). Springer Verlag. https://doi.org/10.1007/978-3-642-39360-0_13
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