A Bootstrapped Modular Learning Approach for Scaling and Generalisation of Grey-Level Corner Detection

Authors:
Rajeev Kumar;Peter Rockett
Affiliations:
-;-
Venue:
AFSS '02 Proceedings of the 2002 AFSS International Conference on Fuzzy Systems. Calcutta: Advances in Soft Computing
Year:
2002

Citing 5
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Abstract

In this paper, we study a bootstrapped learning procedure applied to corner detection using synthetic training data generated from a grey-level model of a corner feature which permits sampling of the pattern space at arbitrary density as well as providing a self-consistent validation set to assess the classifier generalisation. Since adequate learning of the whole mapping by a single neural network is problematic we partition data across modules using bootstrapping and which we then combine by a meta-learning stage. We test the hierarchical classifier on real images and compare results with those obtained by a monolithic network.