Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees

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概要

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• We propose a new method for content-based image retrieval which exploits the similarity measure and indexing structure of totally randomized tree ensembles induced from a set of subwindows randomly extracted from a sample of images. We also present the possibility of updating the model as new images come in, and the capability of comparing new images using a model previously constructed from a different set of images. The approach is quantitatively evaluated on various types of images and achieves high recognition rates despite its conceptual simplicity and computational efficiency.

著者

• Geurts Pierre

  Systems and Modeling Unit, Department of Electrical Engineering and Computer Science, University of Liège

• Marée Raphaël

  GIGA Bioinformatics Platform, University of Liège

• Wehenkel Louis

  Systems and Modeling Unit, Department of Electrical Engineering and Computer Science, University of Liège

関連論文

• Content-based Image Retrieval by Indexing Random Subwindows with Randomized Trees

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