An eyegaze interface is one of the key technologies that serves as an input device in a ubiquitous-computing society. Recently, video-based techniques that do not require specific instruments have been studied. With these approaches, development of an accurate iris-extraction algorithm is very important to realize practical eyegaze tracking. For accurate iris extraction, it is necessary to achieve robustness, high speed, and high accuracy. Conventional iris-extraction algorithms experience difficulties in meeting all these requirements simultaneously. This study proposes an iris-extraction algorithm based on the parametric template matching method to satisfy all these requirements at the same time. The parametric template matching method achieves robustness by interpolating among some templates, and the method attains high accuracy by a subpixel matching technique. High-speed matching can be realized by coarse-to-fine matching. To verify the effectiveness of the proposed algorithm, we performed a basic experiment for eyegaze tracking. We show in this experiment that the processing time is approximately 1/900 of that of our previous method and that accuracy is acceptable with the new method. Then, we apply the proposed algorithm to an eyegaze keyboard, along with an imaging system for improving image quality, and we verify the effectiveness of this approach.
This paper proposes a computer vision system for improving the image quality around a steady gaze point on a display
device. We assume that one observes a localized small area of the displayed image, rather than the whole image, because
of a limited visual angle. The computer vision system consists of two subsystems which are an eyegaze detection
subsystem and an image quality improvement subsystem. The eyegaze detection subsystem tracks a human gaze point on
the display. A tracking algorithm is developed for capturing a human face from a single monocular camera without using
any special devices. The image quality improvement subsystem performs a localized Retinex algorithm. Although the
conventional algorithms contain a large number of complex computations, the localized algorithm is devised for
performing the Retinex computation in high speed for only a localized part within the whole image. The combined
system is developed so that the image quality is improved in real time within just local region around the detected gaze
point. We make an experimental system consisting of an off-the-shelf digital video camera and a personal computer. The
whole performance of the computer vision system is examined experimentally on subjective assessment and processing
time.
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