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231224s2016 xx |||||o 00| ||eng c |
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|a 10.1109/TPAMI.2016.2515606
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|a eng
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| 100 |
1 |
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|a Corneanu, Ciprian Adrian
|e verfasserin
|4 aut
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| 245 |
1 |
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|a Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition
|b History, Trends, and Affect-Related Applications
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|c 2016
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|a Text
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|a Date Completed 09.05.2018
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|a Date Revised 12.11.2023
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|a published: Print-Electronic
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|a Citation Status MEDLINE
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| 520 |
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|a 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
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|a Journal Article
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|a Review
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|a Simon, Marc Oliu
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1 |
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|a Cohn, Jeffrey F
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|a Guerrero, Sergio Escalera
|e verfasserin
|4 aut
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|i Enthalten in
|t IEEE transactions on pattern analysis and machine intelligence
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|g 38(2016), 8 vom: 10. Aug., Seite 1548-68
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