Engagement analysis through computer vision

Author

MacHardy, Z.M. ; Syharath, K. ; Dewan, Prasun

Author_Institution

Comput. Sci. Dept., Univ. of North Carolina at Chapel Hill, Chapel Hill, NC, USA

fYear

2012

fDate

14-17 Oct. 2012

Firstpage

535

Lastpage

539

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; distance learning; distributed processing; face recognition; learning (artificial intelligence); real-time systems; audience engagement level; audience member faces; computer vision; distance education; distance lecturing; distributed online communication; engagement analysis; live online presentation; machine learning; online presenter; real time feedback; Cameras; Emotion recognition; Face; Face recognition; Nose; Software; Videos; Computer Vision; Distance Lecturing; Machine Learning; Online Presentations;

fLanguage

English

Publisher

ieee

Conference_Titel

Collaborative Computing: Networking, Applications and Worksharing (CollaborateCom), 2012 8th International Conference on

Conference_Location

Pittsburgh, PA

Print_ISBN

978-1-4673-2740-4

Type

conf

Filename

6450946