Quick Models for Saccade Amplitude Prediction

This paper presents a new saccade amplitude prediction model. The model is based on a Kalman filter and regression analysis. The aim of the model is to predict a saccade's am-plitude extremely quickly, i.e., within two eye position samples at the onset of a saccade. Specifically, the paper expl...

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Bibliographic Details
Main Authors: Oleg V. Komogortsev (Author), Young Sam Ryu (Author), Do H. Koh (Author)
Format: Book
Published: Bern Open Publishing, 2009-06-01T00:00:00Z.
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Summary:This paper presents a new saccade amplitude prediction model. The model is based on a Kalman filter and regression analysis. The aim of the model is to predict a saccade's am-plitude extremely quickly, i.e., within two eye position samples at the onset of a saccade. Specifically, the paper explores saccade amplitude prediction considering one or two sam-ples at the onset of a saccade. The models' prediction performance was tested with 35 subjects. The amplitude accuracy results yielded approximately 5.26° prediction error, while the error for direction prediction was 5.3% for the first sample model and 1.5% for the two samples model. The practical use of the proposed model lays in the area of real-time gaze-contingent compression and extreme eye-gaze aware interaction applications. The paper provides theoretical evaluation of the benefits of saccade amplitude prediction to the gaze-contingent multimedia compression, estimating a 21% improvement in com-pression for short network delays.
Item Description:10.16910/jemr.3.1.1
1995-8692