Incremental learning of nonparametric Bayesian mixture models

@article{Gomes2008IncrementalLO,
  title={Incremental learning of nonparametric Bayesian mixture models},
  author={Ryan Gomes and Max Welling and Pietro Perona},
  journal={2008 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2008},
  pages={1-8}
}
Clustering is a fundamental task in many vision applications. To date, most clustering algorithms work in a batch setting and training examples must be gathered in a large group before learning can begin. Here we explore incremental clustering, in which data can arrive continuously. We present a novel incremental model-based clustering algorithm based on nonparametric Bayesian methods, which we call memory bounded variational Dirichlet process (MB-VDP). The number of clusters are determined… CONTINUE READING
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