3D facial expression recognition using nonrigid CPD registration method
| Autor: | Imen Hamrouni Trimech, Najoua Essoukri Ben Amara, Ahmed Maalej |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Facial expression
Computer science business.industry Dimensionality reduction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION 020207 software engineering Pattern recognition 02 engineering and technology Solid modeling Facial recognition system Support vector machine ComputingMethodologies_PATTERNRECOGNITION Transformation (function) Facial expression recognition Computer Science::Computer Vision and Pattern Recognition 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Computer vision Artificial intelligence business Coherent point drift |
| Zdroj: | 2016 7th International Conference on Sciences of Electronics, Technologies of Information and Telecommunications (SETIT). |
| DOI: | 10.1109/setit.2016.7939917 |
| Popis: | In this paper we present a novel approach for 3D facial expression recognition based on a registration method. The used registration method, called the Coherent Point Drift (CPD), is applied to estimate complex non-linear and nonrigid transformation between 3D facial surfaces. The computed transformation allows to recover shape deformations that are induced by facial expression variations. Machine learning is applied using Dimensionality reduction methods in order to promote the computational efficiency and Support Vector Machine (SVM) for classification. The obtained experimental results show that our method achieves promising recognition rates on Bhosphorus database. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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