G
Gwen Littlewort
Researcher at University of California, San Diego
Publications - 38
Citations - 5590
Gwen Littlewort is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Facial expression & Facial Action Coding System. The author has an hindex of 26, co-authored 38 publications receiving 5240 citations.
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Proceedings ArticleDOI
Recognizing facial expression: machine learning and application to spontaneous behavior
Marian Stewart Bartlett,Gwen Littlewort,Mark G. Frank,Claudia Lainscsek,Ian Fasel,Javier R. Movellan +5 more
TL;DR: The system operates in real-time, and obtained 93% correct generalization to novel subjects for a 7-way forced choice on the Cohn-Kanade expression dataset, and has a mean accuracy of 94.8%.
Proceedings ArticleDOI
The computer expression recognition toolbox (CERT)
Gwen Littlewort,Jacob Whitehill,Tingfan Wu,Ian Fasel,Mark G. Frank,Javier R. Movellan,Marian Stewart Bartlett +6 more
TL;DR: The Computer Expression Recognition Toolbox (CERT), a software tool for fully automatic real-time facial expression recognition, is presented and officially released for free academic use.
Proceedings ArticleDOI
Real Time Face Detection and Facial Expression Recognition: Development and Applications to Human Computer Interaction.
TL;DR: A novel combination of Adaboost and SVM's enhances performance and the outputs of the classifier change smoothly as a function of time, providing a potentially valuable representation to code facial expression dynamics in a fully automatic and unobtrusive manner.
Journal ArticleDOI
Automatic Recognition of Facial Actions in Spontaneous Expressions
Marian Stewart Bartlett,Gwen Littlewort,Mark G. Frank,Claudia Lainscsek,Ian Fasel,Javier R. Movellan +5 more
TL;DR: A user independent fully automatic system for real time recognition of facial actions from the Facial Action Coding System (FACS) automatically detects frontal faces in the video stream and coded each frame with respect to 20 Action units.
Journal ArticleDOI
Dynamics of facial expression extracted automatically from video
TL;DR: An end-to-end system that provides facial expression codes at 24 frames per second and animates a computer generated character and applies the system to fully automated facial action coding, the best performance reported so far on these datasets.