Ingemar J. Cox, Matt L. Miller, Stephen M. Omohundro, Peter N. Yianilos  Home/Search
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Abstract: This paper addresses how the effectiveness of a contentbased, multimedia information retrieval system can be measured, and how such a system should best use response feedback in performing searches. We propose a simple, quantifiable measure of an image retrieval system's effectiveness, "target testing", in which effectiveness is measured as the average number of images that a user must examine in searching for a given random target. We describe an initial version of PicHunter, a retrieval... (Update)
Context of citations to this paper: More
...images is most similar to that of the user s judgements is returned as the tool that best matches the user s perception. In PicHunter [4, 5], the user s relevance judgements are used to search for the target image. Predictions made using Bayesian learning based on a...
...be a two dimensional image pixel array. The local feature F can be the value of the n color channels [17] the gradient, an edge map [8] 3] [2] or some invariant grey values [13] Therefore the image A is a subset of R R n . The image is partitioned into L subsets A l with...
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BibTeX entry: (Update)
I. J. Cox, M. L. Miller, S. M. Omohundro, and P. N. Yianilos. Target testing and the pichunter bayesian multimedia retrieval system. In Advanced Digital Libraries Forum, Washington D.C., May. http://citeseer.ist.psu.edu/cox96target.html More
@inproceedings{ cox96target,
author = "Ingemar J. Cox and Matt L. Miller and Stephen M. Omohundro and Peter N. Yianilos",
title = "Target Testing and the PicHunter Bayesian Multimedia Retrieval System",
booktitle = "Advances in Digital Libraries",
pages = "66-75",
year = "1996",
url = "citeseer.ist.psu.edu/cox96target.html" }
Citations (may not include all citations):9 Corel Corp (context) - photo
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