3D Facial Expression Recognition Method Based on Local Curvature
| Autor: | Yong-Qiang Cheng, Jin-Wei Wang |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Feature vector Feature extraction ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Pattern recognition Curvature Facial recognition system Expression (mathematics) ComputingMethodologies_PATTERNRECOGNITION Face (geometry) Feature (machine learning) Point (geometry) Artificial intelligence business |
| Zdroj: | 2019 IEEE International Conference of Intelligent Applied Systems on Engineering (ICIASE). |
| DOI: | 10.1109/iciase45644.2019.9074024 |
| Popis: | In order to improve the recognition rate and recognition speed of 3D facial expression recognition, the 3D facial expression recognition method is proposed by local curvature in this paper. First, the tip point of the nose is extracted by the face center profile, with the tip point of the nose as the reference point, searching for search windows of other feature points and automatically extract feature points through local curvature in its window. These feature points are composed into feature vector. Finally, K-means algorithm is adopted to expression classification. The theoretical analysis and experimental results both show that this method has greatly improve the recognition rate and recognition speed of 3D facial expression recognition. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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