Abstract
Automatic facial expression recognition (FER) played more and more important role in recent years for its wide range of potential applications. So, as one of the challenging tasks in intelligent system, it still has many questions need to be deeply researched. Taking into account the importance of eyes and mouth for FER and the outstanding performance of local binary pattern (LBP) to extract local textures, a representation model for facial expressions based on feature blocks and LBP descriptor is proposed. The strategies of feature blocks obtaining and LBP feature extracting are analyzed in details and the recognition experiment is conducted. Experimental result shows that this algorithm has good performance.
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Wang, W., Chang, F. (2014). Facial Expression Recognition Based on Feature Block and Local Binary Pattern. In: Pan, L., Păun, G., Pérez-Jiménez, M.J., Song, T. (eds) Bio-Inspired Computing - Theories and Applications. Communications in Computer and Information Science, vol 472. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45049-9_72
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DOI: https://doi.org/10.1007/978-3-662-45049-9_72
Publisher Name: Springer, Berlin, Heidelberg
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