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FGR
2011
IEEE

Emotion recognition from an ensemble of features

10 years 1 months ago
Emotion recognition from an ensemble of features
— This work details the authors’ efforts to push the baseline of expression recognition performance on a realistic database. Both subject-dependent and subject-independent emotion recognition scenarios are addressed in this work. These two happen frequently in real life settings. The approach towards solving this problem involves face detection, followed by key point identification, then feature generation and then finally classification. An ensemble of features comprising of Hierarchial Gaussianization (HG), Scale Invariant Feature Transform (SIFT) and Optic Flow have been incorporated. In the classification stage we used SVMs. The classification task has been divided into person specific and person independent emotion recognition. Both manual labels and automatic algorithms for person verification have been attempted. They both give similar performance.
Usman Tariq, Kai-Hsiang Lin, Zhen Li, Xi Zhou, Zha
Added 28 Aug 2011
Updated 28 Aug 2011
Type Journal
Year 2011
Where FGR
Authors Usman Tariq, Kai-Hsiang Lin, Zhen Li, Xi Zhou, Zhaowen Wang, Vuong Le, Thomas S. Huang, Xutao Lv, Tony X. Han
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