Anisotropic Agglomerative Adaptive Mean-Shift

@article{Sawhney2014AnisotropicAA,
  title={Anisotropic Agglomerative Adaptive Mean-Shift},
  author={R. Sawhney and H. Christensen and G. Bradski},
  journal={ArXiv},
  year={2014},
  volume={abs/1411.4102}
}
  • R. Sawhney, H. Christensen, G. Bradski
  • Published 2014
  • Computer Science
  • ArXiv
  • Mean Shift today, is widely used for mode detection and clustering. The technique though, is challenged in practice due to assumptions of isotropicity and homoscedasticity. We present an adaptive Mean Shift methodology that allows for full anisotropic clustering, through unsupervised local bandwidth selection. The bandwidth matrices evolve naturally, adapting locally through agglomeration, and in turn guiding further agglomeration. The online methodology is practical and effecive for low… CONTINUE READING

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