Covariance pooling for facial expression recognition
Classifying facial expressions into different categories requires capturing regional distortions of facial landmarks. We believe that second-order statistics such as covariance is better able to capture such distortions in regional facial features. In this work, we explore the benefits of using a ma...
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Main Authors: | ACHARYA, D., HUANG, Zhiwu, PAUDEL, D., VAN, Gool L. |
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Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2018
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Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/sis_research/6388 https://ink.library.smu.edu.sg/context/sis_research/article/7391/viewcontent/Covariance_Pooling_for_Facial_Expression_Recognition.pdf |
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Institution: | Singapore Management University |
Language: | English |
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