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In this paper, we propose the deep neural network - switching Kalman filter (DNN-SKF) based frameworks for both single modal and multi-modal continuous affective dimension estimation. The DNN-SKF framework firstly models the complex nonlinear relationship between the input (audio, visual, or lexical) features and the affective dimensions via the non-recurrent DNN, then models the temporal dynamics...
We present a framework for combination aware AU intensity recognition. It includes a feature extraction approach that can handle small head movements which does not require face alignment. A three layered structure is used for the AU classification. The first layer is dedicated to independent AU recognition, and the second layer incorporates AU combination knowledge. At a third layer, AU dynamics...
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