MAGiC: A Multimodal Framework for Analysing Gaze in Dyadic Communication

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10.16910jemr.11.6.2.pdf

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2018-01-01

Author

Aydin, Ulku Arslan
Kalkan, Sinan
Acartürk, Cengiz

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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The analysis of dynamic scenes has been a challenging domain in eye tracking research. This study presents a framework, named MAGiC, for analyzing gaze contact and gaze aversion in face-to-face communication. MAGiC provides an environment that is able to detect and track the conversation partner's face automatically, overlay gaze data on top of the face video, and incorporate speech by means of speech-act annotation. Specifically, MAGiC integrates eye tracking data for gaze, audio data for speech segmentation, and video data for face tracking. MAGiC is an open source framework and its usage is demonstrated via publicly available video content and wild pages. We explored the capabilities of MAGiC through a pilot study and showed that it facilitates the analysis of dynamic gaze data by reducing the annotation effort and the time spent for manual analysis of video data.

Subject Keywords

Gaze analysis, Speech analysis, Automatic face detection, Automatic speech segmentation

URI

https://hdl.handle.net/11511/31449

Journal

JOURNAL OF EYE MOVEMENT RESEARCH

DOI

https://doi.org/10.16910/jemr.11.6.2

Collections

Graduate School of Informatics, Article

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Citation Formats

U. A. Aydin, S. Kalkan, and C. Acartürk, “MAGiC: A Multimodal Framework for Analysing Gaze in Dyadic Communication,” JOURNAL OF EYE MOVEMENT RESEARCH, pp. 0–0, 2018, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/31449.