Engagement Analysis Through Computer Vision

Zachary MacHardy; Kenneth Syharath; Prasun Dewan

8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing

Research Article

Engagement Analysis Through Computer Vision

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Cite: BibTeX Plain Text

@INPROCEEDINGS{10.4108/icst.collaboratecom.2012.250429,
    author={Zachary MacHardy and Kenneth Syharath and Prasun Dewan},
    title={Engagement Analysis Through Computer Vision},
    proceedings={8th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing},
    publisher={IEEE},
    proceedings_a={COLLABORATECOM},
    year={2012},
    month={12},
    keywords={computer vision machine learning distance lecturing online presentations},
    doi={10.4108/icst.collaboratecom.2012.250429}
}

Zachary MacHardy
Kenneth Syharath
Prasun Dewan
Year: 2012
Engagement Analysis Through Computer Vision
COLLABORATECOM
ICST
DOI: 10.4108/icst.collaboratecom.2012.250429

Zachary MacHardy¹^,*, Kenneth Syharath¹, Prasun Dewan¹

1: University of North Carolina At Chapel Hill

*Contact email: zmmachar@email.unc.edu

Abstract

As distributed online communication becomes increasingly common, and audiences for live online presentations grow larger, the ability to receive meaningful feedback from audience members who are distant and distributed becomes a necessity. To this end, we have built upon previous work to create a tool that is capable of providing real time feedback to an online presenter about the engagement level of the audience. The tool makes inferences by using computer vision and machine learning techniques to analyze the faces of audience members.

Keywords: computer vision machine learning distance lecturing online presentations

Published: 2012-12-14
Publisher: IEEE

: http://dx.doi.org/10.4108/icst.collaboratecom.2012.250429