Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected In-the-Wild
Computer classification of facial expressions requires large amounts of data and this data needs to reflect the diversity of conditions seen in real applications. Public datasets help accelerate the progress of research by providing researchers with a benchmark resource. We present a comprehensively...
Main Authors: | McDuff, Daniel Jonathan, Senechal, Thibaud, Amr, May, Cohn, Jeffrey F., Picard, Rosalind W., El Kaliouby, Rana |
---|---|
Other Authors: | Massachusetts Institute of Technology. Media Laboratory |
Format: | Article |
Language: | en_US |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2013
|
Online Access: | http://hdl.handle.net/1721.1/80733 https://orcid.org/0000-0002-5661-0022 |
Similar Items
-
Acume: A New Visualization Tool for Understanding Facial Expression and Gesture Data
by: McDuff, Daniel Jonathan, et al.
Published: (2011) -
Crowdsourced data collection of facial responses
by: McDuff, Daniel Jonathan, et al.
Published: (2013) -
Crowdsourcing facial responses to online videos: Extended abstract
by: McDuff, Daniel, et al.
Published: (2017) -
Real-Time Inference of Mental States from Facial Expressions and Upper Body Gestures
by: Baltrusaitis, Tadas, et al.
Published: (2011) -
Predicting Ad Liking and Purchase Intent: Large-Scale Analysis of Facial Responses to Ads
by: Kaliouby, Rana El, et al.
Published: (2017)