eyeView: focus+context views for large group video conferences

Authors:
Tracy Jenkin;Jesse McGeachie;David Fono;Roel Vertegaal
Affiliations:
Queen's University, Kingston ON, Canada;Queen's University, Kingston ON, Canada;Queen's University, Kingston ON, Canada;Queen's University, Kingston ON, Canada
Venue:
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Year:
2005

Citing 11
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Abstract

In this paper, we describe the design of eyeView, a video conferencing system that uses participant looking behavior to determine the size of online video conferencing windows. The system uses an elastic windowing algorithm that enlarges the image of the person most looked at by others, while maintaining a contextual view of other remote participants. eyeView measures interest by gauging whom participants look at using an eye tracker embedded in the display. Users can enter side conversations by looking at each other, and pressing the space bar. Cocktail-party filtering is aided by attenuating audio sources outside the social network constituted by glances between participants. By allocating both screen and audio real estate according to the joint attention of participants, eyeView supports smooth allocation of focus on the speaker, while maintaining awareness of the group.