UIBVFED: Virtual facial expression dataset

PloS One
Miquel Mascaró Oliver, Esperança Amengual Alcover

Abstract

Facial expression classification requires large amounts of data to reflect the diversity of conditions in the real world. Public databases support research tasks providing researchers an appropriate work framework. However, often these databases do not focus on artistic creation. We developed an innovative facial expression dataset that can help both artists and researchers in the field of affective computing. This dataset can be managed interactively by an intuitive and easy to use software application. The dataset is composed of 640 facial images from 20 virtual characters each creating 32 facial expressions. The avatars represent 10 men and 10 women, aged between 20 and 80, from different ethnicities. Expressions are classified by the six universal expressions according to Gary Faigin classification.

References

May 7, 2005·IEEE Transactions on Pattern Analysis and Machine Intelligence·Alice J O'TooleHervé Abdi
Sep 19, 2009·IEEE Transactions on Pattern Analysis and Machine Intelligence·Jacob WhitehillJavier Movellan
May 22, 2010·Proceedings of the ... International Conference on Automatic Face and Gesture Recognition·Ralph GrossSimon Baker
Nov 30, 2011·Frontiers in Human Neuroscience·Bernard M C Stienen, Beatrice de Gelder

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Citations

Sep 2, 2020·Sensors·Vianney Perez-GomezAntonio Marin-Hernandez

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Methods Mentioned

BETA
FACS
feature extraction

Software Mentioned

WebGl
Unity
Autodesk Character Generator
Autodesk
MouthOpen
Genki
FACS
Adobe
PIE
Facial Action Coding System ( FACS )

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