Dynamic Training using Multistage Clustering for Face Recognition

  title={Dynamic Training using Multistage Clustering for Face Recognition},
  author={Marios Kyperountasa and Anastasios Tefasa and Ioannis Pitasa},
  • Marios Kyperountasa, Anastasios Tefasa, Ioannis Pitasa
  • Published 2010
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