Dynamic training using multistage clustering for face recognition

@article{Kyperountas2008DynamicTU,
  title={Dynamic training using multistage clustering for face recognition},
  author={Marios Kyperountas and Anastasios Tefas and Ioannis Pitas},
  journal={Pattern Recognition},
  year={2008},
  volume={41},
  pages={894-905}
}
A novel face recognition algorithm that uses dynamic training in a multistage clustering scheme is presented and evaluated. This algorithm uses discriminant analysis to project the face classes and a clustering algorithm to partition the projected face data, thus forming a set of discriminant clusters. Then, an iterative process creates subsets, whose cardinality is defined by an entropy-based measure, that contain the most useful clusters. The best match to the test face is found when only a… CONTINUE READING
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