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The Roles of Endstopped and Curvature Tuned Computations in a Hierarchical Representation of 2D Shape
Abstract
Computational models of visual processes are of interest in fields such as cybernetics, robotics, computer vision, and others. This chapter argues for the importance of intermediate representation layers in the visual cortex that have direct impact on the next generation of object recognition strategies in computer vision. Biological inspiration - and even biological realism - is currently of great interest in the computer vision community. The authors propose that endstopping and curvature cells are of great importance for shape selectivity and show how their combination can lead to shape selective neurons, providing an approach that does not require learning between early stages based on Gabor or Difference of Gaussian filters and later stages closer to object representations.
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