Decision Prediction Using Visual Patterns

• Autorzy: Qin L. , Zhong N. , Lu S. , Li M.
• Języki publikacji: EN

Abstrakty

EN

Lack of understanding of users' underlying decision making process results in the bottleneck of EB-HCI (eye movement-based human-computer interaction) systems. Meanwhile, considerable findings on visual features of decision making have been derived from cognitive researches over past few years. A promising method of decision prediction in EB-HCI systems is presented in this article, which is inspired by the looking behavior when a user makes a decision. As two features of visual decision making, gaze bias and pupil dilation are considered into judging intensions. This method combines the history of eye movements to a given interface and the visual traits of users. Hence, it improves the prediction performance in a more natural and objective way. We apply the method to an either-or choice making task on the commercial Web pages to test its effectiveness. Although the result shows a good performance only of gaze bias but not of pupil dilation to predict a decision, it proves that hiring the visual traits of users is an effective approach to improve the performance of automatic triggering in EB-HCI systems.

Słowa kluczowe

EN

decision theory; prediction theory; pattern recognition system; human-computer interaction; performance evaluation; feature extraction

• Wydawca: IOS Press
• Czasopismo: Fundamenta Informaticae
• Rocznik: 2013
• Tom: Vol. 127, nr 1-4
• Strony: 545--560
• Opis fizyczny: Bibliogr. 27 poz., rys., wykr.

Twórcy

autor

Qin L.

• International WIC Institute, Beijing University of Technology, Beijing 100124, P.R. China

autor

Zhong N.

• International WIC Institute, Beijing University of Technology, Beijing 100124, P.R. China

autor

Lu S.

• International WIC Institute, Beijing University of Technology, Beijing 100124, P.R. China

autor

Li M.

• International WIC Institute, Beijing University of Technology, Beijing 100124, P.R. China

Bibliografia

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