Abstract
In this paper, we design an Attention Focus Kalman Filter (AFKF) - a framework that offers interaction capabilities by constructing an eye-movement language, provides real-time perceptual compression through Human Visual System (HVS) modeling, and improves system’s reliability. These goals are achieved by an AFKF through identification of basic eye-movement types in real-time, the prediction of a user’s perceptual attention focus, and the use of the eye’s visual sensitivity function and eye-position data signal de-noising.
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Komogortsev, O.V., Khan, J.I. (2007). Kalman Filtering in the Design of Eye-Gaze-Guided Computer Interfaces. In: Jacko, J.A. (eds) Human-Computer Interaction. HCI Intelligent Multimodal Interaction Environments. HCI 2007. Lecture Notes in Computer Science, vol 4552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73110-8_74
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DOI: https://doi.org/10.1007/978-3-540-73110-8_74
Publisher Name: Springer, Berlin, Heidelberg
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