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Abstract: We present an approach for image database retrieval using a very large number of highly-selective features and simple on-line learning. Our approach is predicated on the assumption that each image is generated by a sparse set of visual "causes" and that images which are visually similar share causes. We propose a mechanism for generating a large number of complex features which capture some aspects of this causal structure. Boosting is used to learn simple and efficient classifiers in this... (Update)
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BibTeX entry: (Update)
@misc{ tieu-boosting,
author = "Kinh H. Tieu and Paul Viola",
title = "Boosting Image Database Retrieval",
url = "citeseer.ist.psu.edu/tieu99boosting.html" }
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