Evolving Visual Feature Detectors

Authors:
Tony Belpaeme
Affiliations:
-
Venue:
ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life
Year:
1999

Citing 2
Cited 1

SEEMORE: combining color, shape, and texture histogramming in a neurally inspired approach to visual object recognition

Neural Computation
Evolving Visual Feature Detectors

ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life

Evolving Visual Feature Detectors

ECAL '99 Proceedings of the 5th European Conference on Advances in Artificial Life

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Abstract

This paper describes the generation and selection of visual feature detectors. The feature detectors are randomly generated, and are built out of components, some having functionality inspired on observations of animal visual pathways. The input for the feature detectors consists of non-synthetic images, while the selectionist pressure comes from the amount of information the feature detectors generate. The experimental setup is described and some results are given.