Titlebook: Image and Video Retrieval; International Confer Michael S. Lew,Nicu Sebe,John P. Eakins Conference proceedings 2002 Springer-Verlag Berlin

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0302-9743 Overview: Includes supplementary material: 978-3-540-43899-1978-3-540-45479-3Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Challenges of Image and Video Retrievalhas been done in finding images and videos in large digital collections. In fact, if we examine the most frequently used image and video retrieval systems (i.e. www.google.com) we find that they are typically oriented around text searches where manual annotation was already performed.

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Non-retrieval: Blocking Pornographic Imagesnd modern classifiers. We find the artificial neural network offers a statistically significant improvement. In all cases the error rate is too high unless deployed sensitively so we show how such a system may be built into a commercial environment.

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Image Retrieval Methods for a Database of Funeral Monumentsts from English churches. The technique, which can be applied to large databases, allows an arbitrary patch of a reference image to be matched to patches of each database image at a range of scales and positions. We investigate the use of nonlinear preprocessing to reduce the influence of lighting and surface reflectance on the match results.

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