Polynomial based texture representation for facial expression recognition
| Autor: | Philippe Carré, Pascal Bourdon, Bertrand Augereau, Cristina Bordei |
|---|---|
| Přispěvatelé: | XLIM (XLIM), Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS), SIC (XLIM-SIC), Université de Poitiers-XLIM (XLIM), Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS)-Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS) |
| Rok vydání: | 2014 |
| Předmět: |
Facial expression
Polynomial Texture representation Pixel Basis (linear algebra) business.industry ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition State (functional analysis) Image (mathematics) Facial expression recognition [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] Computer vision Artificial intelligence business Mathematics |
| Zdroj: | ICASSP Proceedings of International Conference on Acoustics, Speech, and Signal Processing-IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2014 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), May 2014, Florence, Italy. pp.529 |
| DOI: | 10.1109/icassp.2014.6853652 |
| Popis: | International audience; In this paper, we propose a new polynomial based texture representation method for extracting information about facial expressions. While many appearance-based methods have been proposed over the years to improve the performance of facial expression recognition, most descriptors are usually unable to both provide precise multi-scale / multi-orientation analysis and handle the redundancy problem effectively. We will explain how coefficients obtained from polynomial projections of pixel intensities on a complete basis can be used for compact, hierarchical image approximation and structural analysis. We have tested our approach on two publicly available databases and achieved encouraging results comparable to the state of the art. |
| Databáze: | OpenAIRE |
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