David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
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Nearest-neighbor correlation-based similarity computation in the space of outputs of complex-type receptive elds can support robust recognition of 3D objects. Our experiments with four collections of objects resulted in mean recognition rates between 84% (for subordinate-level discrimination among 15 quadruped animal shapes) and 94% (for basic-level recognition of 20 everyday objects), over a 40 40 range of viewpoints, centered on a stored canonical view and related to it by rotations in depth. This result has interesting implications for the design of a front end to an arti cial object recognition system, and for the understanding of the faculty of object recognition in primate vision.
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