Combining Multiple Kernel Methods on Riemannian Manifold for Emotion Recognition in the Wild

@inproceedings{Liu2014CombiningMK,
  title={Combining Multiple Kernel Methods on Riemannian Manifold for Emotion Recognition in the Wild},
  author={Mengyi Liu and Ruiping Wang and Shaoxin Li and Shiguang Shan and Zhiwu Huang and Xilin Chen},
  booktitle={ICMI},
  year={2014}
}
In this paper, we present the method for our submission to the Emotion Recognition in the Wild Challenge (EmotiW 2014). The challenge is to automatically classify the emotions acted by human subjects in video clips under real-world environment. In our method, each video clip can be represented by three types of image set models (i.e. linear subspace, covariance matrix, and Gaussian distribution) respectively, which can all be viewed as points residing on some Riemannian manifolds. Then… CONTINUE READING
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