Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications

Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is n...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 2016-08, Vol.38 (8), p.1548-1568
Main Authors: Corneanu, C. A., Oliu Simon, Marc, Cohn, Jeffrey F., Escalera Guerrero, Sergio
Format: Article
Language:English
Subjects:
affect
Algorithms
Emotion recognition
Encoding
Face
Facial Expression
Humans
Iron
multimodal
Pattern Recognition, Automated
RGB
Taxonomy
thermal
Three-dimensional displays
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Facial expressions are an important way through which humans interact socially. Building a system capable of automatically recognizing facial expressions from images and video has been an intense field of study in recent years. Interpreting such expressions remains challenging and much research is needed about the way they relate to human affect. This paper presents a general overview of automatic RGB, 3D, thermal and multimodal facial expression analysis. We define a new taxonomy for the field, encompassing all steps from face detection to facial expression recognition, and describe and classify the state of the art methods accordingly. We also present the important datasets and the bench-marking of most influential methods. We conclude with a general discussion about trends, important questions and future lines of research.
ISSN:0162-8828
1939-3539
2160-9292
DOI:10.1109/TPAMI.2016.2515606