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Online Behavioral Analysis with Application to Emotion State Identification
Published 27 Feb 2021 in cs.CV and cs.LG | (2103.00356v1)
Abstract: In this paper, we propose a novel discriminative model for online behavioral analysis with application to emotion state identification. The proposed model is able to extract more discriminative characteristics from behavioral data effectively and find the direction of optimal projection efficiently to satisfy requirements of online data analysis, leading to better utilization of the behavioral information to produce more accurate recognition results.
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