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Интеллектуальная Система Тематического Исследования НАукометрических данных |
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Automatic Detection of Gaze Convergence in Multimodal Collaboration: A Dual Eye-Tracking Technologyстатья Исследовательская статья
- Авторы: Anna Shvarts, Andrey Stepanov, Dmitry Chumachenko
- Журнал: The Russian Journal of Cognitive Science
- Том: 5
- Номер: 3
- Год издания: 2018
- Первая страница: 4
- Последняя страница: 17
- Аннотация: The paper analyses the advantages and limitations of the current technical solutions for dual eye-tracking (DUET) in relation to the research questions from educational science about joint attention in a multimodal teaching/ learning collaboration. The insufficiency of the current systems for the analysis of multimodal collaboration is stated as the reviewed systems do not allow researchers to relate a participant’s eye movements to the video from their joint performance and accompanying gestures without time consuming manual coding. We describe a system of two low-cost Pupil-Labs eye- trackers and propose an open source utility DUET for Pupil that automatically produces synchronized gaze data in the shared system of coordinates. The data are available in the form of a video from the surface that is overlaid by gaze paths with supplementary sound waveforms and as textual data with synchronized coordinates of the two gazes. Our empirical evaluation of this technological solution reports 1.27 ° of visual angle as the spatial accuracy of the system after post-hoc calibration. The advantages, limitations, and further possible enhancments of the system are discussed.
- Добавил в систему: Чумаченко Дмитрий Валерьевич
Прикрепленные файлы
| № | Имя | Описание | Имя файла | Размер | Добавлен |
|---|---|---|---|---|---|
| 1. | Полный текст | Automatic_Detection_of_Gaze_Convergence.pdf | 565,8 КБ | 28 августа 2019 [ChumachenkoDV] |