The MCF Model: Utilizing Multiple Colours for Face Recognition
Finding a good color space is one of the main research goals for color face recognition. Existing research shows that RGB can improve over gray-scale, while some other color spaces (YQCr for instance) can improve over RGB. However, all developed color models consist of only three color components tr...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference Paper |
| Published: |
IEEE
2011
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| Online Access: | http://hdl.handle.net/20.500.11937/35748 |
| Summary: | Finding a good color space is one of the main research goals for color face recognition. Existing research shows that RGB can improve over gray-scale, while some other color spaces (YQCr for instance) can improve over RGB. However, all developed color models consist of only three color components transformed linearly from RGB. Since three colors may not capture sufficient information for solving complex face recognition problems and nonlinear transformed colors usually encode very different information, this paper investigates the feasibility and effectiveness of using more than three colors including some non-linear color spaces. We propose a novel color combination algorithm namely the Multiple Color Fusion (MCF) model to utilize multiple colors. Experiment 4 on FRGC2 is conducted to demonstrate the effectiveness of MCF. In particular, MCF outperforms any existing three-color based methods by at least 3% and improves over RGB by 8%. |
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