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Action unit classification for facial expression recognition using active learning and SVM
Article utilizing active learning and support vector machine (SVM) algorithms to classify facial action units (AU) for human facial expression recognition. Experimental results show that the proposed algorithm can effectively suppress correlated noise and achieve higher recognition rates than principal component analysis and a human observer on seven different facial expressions.
Date:
April 4, 2021
Creator:
Yao, Li; Wan, Yan & Xu, Bugao
System:
The UNT Digital Library