VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam
Shahed Anzarus Sabab, Mohammad Ridwan Kabir, Sayed Rizban Hussain, Hasan Mahmud, Husne Ara Rubaiyeat, Md. Kamrul Hasan · IEEE Access · 2022
Human intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing eithertextualorgraphicalinformation, intention to perceive desired information is subjective and strongly connected with eye gaze. In this work, we determine such intention by analyzing real-time eye gaze data with a low-cost regular webcam. We extracted unique features (e.g.,Fixation Count, Eye Movement Ratio) from the eye gaze data of 31 participants to generate a dataset containing 124 samples of visual intention for perceivingtextualorgraphicalinformation, labeled as eitherTEXTorIMAGE, having 48.39% and 51.61% distribution, respectively. Using this dataset, we analyzed 5 classifiers, includingSupport Vector Machine(SVM) (Accuracy: 92.19%). Using the trainedSVM, we investigated the variation of visual intention among 30 participants, distributed in 3 age groups, and found out that young users were more leaned towardsgraphicalcontents whereas older adults felt more interested intextualones. This finding suggests that real-time eye gaze data can be a potential source of identifying visual intention, analyzing which intention aware interactive interfaces can be designed and developed to facilitate human cognition.