Abstract
Human eye blinks include voluntary (conscious) blinks and involuntary (unconscious) blinks. If the voluntary blinks can be detected automatically, a decision can be made whether to use the eye blink as application input. If the entire eye blink process is captured, the wave pattern of an eye blink can be generated. We have developed a new method for measuring the wave pattern of an eye blink. Based on these wave patterns, feature parameters for eye blink type classification can be estimated. To develop an eye blink input interface suitable for practical use, the interface system utilizes a standard video camera, such as an NTSC-based model. Specifically, this system requires feature parameters that can be estimated by a standard video camera. In addition, if other application programs are executed while the eye-blink detection program is in use, the video capture sampling rate is decreased. In this paper, we present the feature parameters of voluntary and involuntary eye blinks, and discuss the changes that occur when the sampling rate is decreased.
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