NDLI: FaceTube: predicting personality from facial expressions of emotion in online conversational video

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FaceTube: predicting personality from facial expressions of emotion in online conversational video

Content Provider	ACM Digital Library
Author	Teijeiro-Mosquera, Lucía Gatica-Perez, Daniel Biel, Joan-Isaac
Abstract	The advances in automatic facial expression recognition make possible to mine and characterize large amounts of data, opening a wide research domain on behavioral understanding. In this paper, we leverage the use of a state-of-the-art facial expression recognition technology to characterize users of a popular type of online social video, conversational vlogs. First, we propose the use of several activity cues to characterize vloggers based on frame-by-frame estimates of facial expressions of emotion. Then, we present results for the task of automatically predicting vloggers' personality impressions using facial expressions and the Big-Five traits. Our results are promising, specially for the case of the Extraversion impression, and in addition our work poses interesting questions regarding the representation of multiple natural facial expressions occurring in conversational video.
Starting Page	53
Ending Page	56
Page Count	4
File Format	PDF
ISBN	9781450314671
DOI	10.1145/2388676.2388689
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2012-10-22
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Facial expressions Youtube Vlogs Personality prediction
Content Type	Text
Resource Type	Article

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