VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam
Human intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing either <italic>textual</italic> or <italic>graphical</italic> information, intention to perceive desired information is subjective and strongly co...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/9813721/ |
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| author | Shahed Anzarus Sabab Mohammad Ridwan Kabir Sayed Rizban Hussain Hasan Mahmud Husne Ara Rubaiyeat Md. Kamrul Hasan |
| author_facet | Shahed Anzarus Sabab Mohammad Ridwan Kabir Sayed Rizban Hussain Hasan Mahmud Husne Ara Rubaiyeat Md. Kamrul Hasan |
| author_sort | Shahed Anzarus Sabab |
| collection | DOAJ |
| description | Human intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing either <italic>textual</italic> or <italic>graphical</italic> 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., <italic>Fixation Count, Eye Movement Ratio</italic>) from the eye gaze data of 31 participants to generate a dataset containing 124 samples of visual intention for perceiving <italic>textual</italic> or <italic>graphical</italic> information, labeled as either <italic>TEXT</italic> or <italic>IMAGE</italic>, having 48.39% and 51.61% distribution, respectively. Using this dataset, we analyzed 5 classifiers, including <italic>Support Vector Machine</italic> (<italic>SVM</italic>) (<italic>Accuracy</italic>: 92.19%). Using the trained <italic>SVM</italic>, 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 <italic>graphical</italic> contents whereas older adults felt more interested in <italic>textual</italic> 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. |
| first_indexed | 2024-04-13T04:37:40Z |
| format | Article |
| id | doaj.art-485ec59b56ad48a4aa726e3ca66642a7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-13T04:37:40Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-485ec59b56ad48a4aa726e3ca66642a72022-12-22T03:02:07ZengIEEEIEEE Access2169-35362022-01-0110707797079210.1109/ACCESS.2022.31879699813721VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost WebcamShahed Anzarus Sabab0Mohammad Ridwan Kabir1https://orcid.org/0000-0002-9631-1836Sayed Rizban Hussain2Hasan Mahmud3https://orcid.org/0000-0003-4375-6943Husne Ara Rubaiyeat4Md. Kamrul Hasan5https://orcid.org/0000-0003-1295-7945Systems and Software Laboratory (SSL), Islamic University of Technology (IUT), Gazipur, BangladeshSystems and Software Laboratory (SSL), Islamic University of Technology (IUT), Gazipur, BangladeshSystems and Software Laboratory (SSL), Islamic University of Technology (IUT), Gazipur, BangladeshSystems and Software Laboratory (SSL), Islamic University of Technology (IUT), Gazipur, BangladeshNatural Science Group, National University, Bangladesh, Gazipur, BangladeshSystems and Software Laboratory (SSL), Islamic University of Technology (IUT), Gazipur, BangladeshHuman intention is an internal, mental characterization for acquiring desired information. From interactive interfaces containing either <italic>textual</italic> or <italic>graphical</italic> 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., <italic>Fixation Count, Eye Movement Ratio</italic>) from the eye gaze data of 31 participants to generate a dataset containing 124 samples of visual intention for perceiving <italic>textual</italic> or <italic>graphical</italic> information, labeled as either <italic>TEXT</italic> or <italic>IMAGE</italic>, having 48.39% and 51.61% distribution, respectively. Using this dataset, we analyzed 5 classifiers, including <italic>Support Vector Machine</italic> (<italic>SVM</italic>) (<italic>Accuracy</italic>: 92.19%). Using the trained <italic>SVM</italic>, 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 <italic>graphical</italic> contents whereas older adults felt more interested in <italic>textual</italic> 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.https://ieeexplore.ieee.org/document/9813721/Human-computer interactionvisual intention detectioneye gazeKalman filteringsaccadesfixation |
| spellingShingle | Shahed Anzarus Sabab Mohammad Ridwan Kabir Sayed Rizban Hussain Hasan Mahmud Husne Ara Rubaiyeat Md. Kamrul Hasan VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam IEEE Access Human-computer interaction visual intention detection eye gaze Kalman filtering saccades fixation |
| title | VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam |
| title_full | VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam |
| title_fullStr | VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam |
| title_full_unstemmed | VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam |
| title_short | VIS-iTrack: Visual Intention Through Gaze Tracking Using Low-Cost Webcam |
| title_sort | vis itrack visual intention through gaze tracking using low cost webcam |
| topic | Human-computer interaction visual intention detection eye gaze Kalman filtering saccades fixation |
| url | https://ieeexplore.ieee.org/document/9813721/ |
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