Web-Scale Image Clustering Revisited

@article{Avrithis2015WebScaleIC,
  title={Web-Scale Image Clustering Revisited},
  author={Yannis S. Avrithis and Yannis Kalantidis and Evangelos Anagnostopoulos and Ioannis Z. Emiris},
  journal={2015 IEEE International Conference on Computer Vision (ICCV)},
  year={2015},
  pages={1502-1510}
}
Large scale duplicate detection, clustering and mining of documents or images has been conventionally treated with seed detection via hashing, followed by seed growing heuristics using fast search. Principled clustering methods, especially kernelized and spectral ones, have higher complexity and are difficult to scale above millions. Under the assumption of documents or images embedded in Euclidean space, we revisit recent advances in approximate k-means variants, and borrow their best… CONTINUE READING
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