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Machine learning / Data mining / Detection theory / Receiver operating characteristic / Naive Bayes classifier / Affective computing / Smile / Gain / Affect / Statistics / Statistical classification / Feeling


Predicting Online Media Effectiveness Based on Smile Responses Gathered Over the Internet Daniel McDuff, Rana el Kaliouby, David Demirdjian and Rosalind Picard I. I NTRODUCTION The face has been shown to communicate disc
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Document Date: 2014-10-31 18:01:12

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File Size: 2,70 MB

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Company

Netflix / Hulu / Volkswagen / Affectiva Inc. / Google Inc. / Media Laboratory / /

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Facility

Media Laboratory / Massachusetts Institute of Technology / /

IndustryTerm

advertising success / Internet using platforms / advertising likeability / online video / Computer vision systems / online videos / demirdji@csail.mit.edu Online Content / internet video ads / smile prediction algorithm / web-based framework / Internet Daniel McDuff / Internet videos / online content / smile detection algorithm / advertising effectiveness / energy / /

Organization

Massachusetts Institute of Technology / Pattern Analysis and Machine Intelligence / /

Person

P. Neijens / David Demirdjian / Rana el Kaliouby / Oliver Wilder-Smith / L. Van Meurs / Richard Sadowsky / All smiles / Rosalind Picard / Jay Turcot / Brian Staats / E. Smit / Jon Bruner / /

ProvinceOrState

Massachusetts / /

SportsEvent

Super Bowl / /

Technology

smile detection algorithm / smile prediction algorithm / gesture recognition / /

URL

http /

SocialTag