Face recognition using supervised probabilistic principal component analysis mixture model in dimensionality reduction without loss framework
In this study, first a supervised version for probabilistic principal component analysis mixture model is proposed. Using this model, local linear underlying manifolds of data samples are obtained. These underlying manifolds are used in a dimensionality reduction without loss framework, for face rec...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-04-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2014.0434 |