JOURNAL ARTICLE
Facial expression recognition from static images
Bilge Suheyla AkkocaMuhittin Gökmen
Year: 2014 Vol: 7584 Pages: 1291-1294
Abstract
In this study, a cascaded structure includes algorithms of Local Zernike Moments, Local XOR Patterns and Global Zernike Moments is used for Facial Expression Recognition. 10 patches are specified on the images in CK+ dataset and over those pathces 3 methods are applied respectively. By concataneting of the moment coefficients, the feature vector generated and classified with Support Vector Machines.
Keywords:
Zernike polynomials Pattern recognition (psychology) Artificial intelligence Support vector machine Moment (physics) Computer science Velocity Moments Feature extraction Feature (linguistics) Facial expression Computer vision Feature vector Expression (computer science) Facial expression recognition Facial recognition system Physics Optics
Metrics
2
Cited By
0.24
FWCI (Field Weighted Citation Impact)
13
Refs
0.60
Citation Normalized Percentile
Is in top 1%
Is in top 10%
Citation History
Topics
Face and Expression Recognition
Physical Sciences → Computer Science → Computer Vision and Pattern Recognition
Emotion and Mood Recognition
Social Sciences → Psychology → Experimental and Cognitive Psychology
Neural Networks and Applications
Physical Sciences → Computer Science → Artificial Intelligence
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