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arXiv 2202.02587cs.HCcs.CVcs.LG

VIS-iTrack: Visual Intention through Gaze Tracking using Low-Cost Webcam

Islamic University of Technology(伊斯兰技术大学);University of Manitoba(曼尼托巴大学);National University, Bangladesh(孟加拉国国立大学)

Shahed Anzarus Sabab, Mohammad Ridwan Kabir, Sayed Rizban Hussain, Hasan Mahmud, Md. Kamrul Hasan, Husne Ara Rubaiyeat

英文摘要:

Human intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing either textual or graphical information, 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 perceiving textual or graphical information, labeled as either TEXT or IMAGE, having 48.39% and 51.61% distribution, respectively. Using this dataset, we analyzed 5 classifiers, including Support Vector Machine (SVM) (Accuracy: 92.19%). Using the trained SVM, we investigated the variation of visual intention among 30 participants, distributed in 3 age groups, and found out that young users were more leaned towards graphical contents whereas older adults felt more interested in textual ones. 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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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