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FGR
2011
IEEE

Facial action unit recognition with sparse representation

9 years 1 months ago
Facial action unit recognition with sparse representation
This paper presents a novel framework for recognition of facial action unit (AU) combinations by viewing the classification as a sparse representation problem. Based on this framework, we represent a facial image exhibiting the combination of AUs as a sparse linear combination of basis constituting an overcomplete dictionary. We build an overcomplete dictionary whose main elements are mean Gabor features of AU combinations under examination. The other elements of the dictionary are randomly sampled from a distribution (e.g., Gaussian distribution) that guarantees sparse signal recovery. Afterwards, by solving L1-norm minimization, a facial image is represented as a sparse vector which is used to distinguish various AU patterns. After calculating the sparse representation, the classification problem is simply viewed as a rank maximal problem. The index of the maximal value of the sparse vector is regarded as the class label of the facial image under test. Extensive experiments on the Co...
Mohammad H. Mahoor, Mu Zhou, Kevin L. Veon, Seyed
Added 28 Aug 2011
Updated 28 Aug 2011
Type Journal
Year 2011
Where FGR
Authors Mohammad H. Mahoor, Mu Zhou, Kevin L. Veon, Seyed Mohammad Mavadati, Jeffrey F. Cohn
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