Kernel Maximum Mean Discrepancy for Region Merging Approach

@inproceedings{Slimene2013KernelMM,
  title={Kernel Maximum Mean Discrepancy for Region Merging Approach},
  author={Alya Slimene and Ezzeddine Zagrouba},
  booktitle={CAIP},
  year={2013}
}
Kernel methods are becoming increasingly challenging for use in a wide variety of computer vision applications. This paper introduces the use of Kernel MaximumMean Discrepancy (KMMD) for region merging process. KMMD is a recent unsupervised kernel-based method commonly used in analysing and comparing distributions. We propose a region merging approach based… CONTINUE READING