Facial expression recognition using bag of distances |
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Authors: | Fu-Song Hsu Wei-Yang Lin Tzu-Wei Tsai |
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Affiliation: | 1. Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan 2. Department of Multimedia Design, National Taichung University of Science and Technology, Taichung, Taiwan
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Abstract: | The automatic recognition of facial expressions is critical to applications that are required to recognize human emotions, such as multimodal user interfaces. A novel framework for recognizing facial expressions is presented in this paper. First, distance-based features are introduced and are integrated to yield an improved discriminative power. Second, a bag of distances model is applied to comprehend training images and to construct codebooks automatically. Third, the combined distance-based features are transformed into mid-level features using the trained codebooks. Finally, a support vector machine (SVM) classifier for recognizing facial expressions can be trained. The results of this study show that the proposed approach outperforms the state-of-the-art methods regarding the recognition rate, using a CK+ dataset. |
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