Local feature analysis : a general statistical theory for object representation

@inproceedings{Penev2007LocalFA,
  title={Local feature analysis : a general statistical theory for object representation},
  author={Penio S. Penev and Joseph J. Atick},
  year={2007}
}
Low-dimensional representations of sensory signals are key to solving many of the computational problems encountered in high-level vision. Principal component analysis (PCA) has been used in the past to derive practically useful compact representations for different classes of objects. One major objection to the applicability of PCA is that it invariably leads to global, non-topographic representations that are not amenable to further processing and are not biologically plausible. In this paper… CONTINUE READING