SEEMORE: Combining Color, Shape, and Texture Histogramming in a Neurally Inspired Approach to Visual Object Recognition

@article{Mel1997SEEMORECC,
  title={SEEMORE: Combining Color, Shape, and Texture Histogramming in a Neurally Inspired Approach to Visual Object Recognition},
  author={Bartlett W. Mel},
  journal={Neural Computation},
  year={1997},
  volume={9},
  pages={777-804}
}
Severe architectural and timing constraints within the primate visual system support the conjecture that the early phase of object recognition in the brain is based on a feedforward feature-extraction hierarchy. To assess the plausibility of this conjecture in an engineering context, a difficult three-dimensional object recognition domain was developed to challenge a pure feedforward, receptive-field based recognition model called SEEMORE. SEEMORE is based on 102 viewpoint-invariant nonlinear… CONTINUE READING
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