| ECVision indexed and annotated bibliography of cognitive computer vision publications This bibliography was created by Hilary Buxton and Benoit Gaillard, University of Sussex, as part of ECVision Specific Action 8-1 The complete text version of this BibTeX file is available here: ECVision_bibliography.bib
J. Vogel and B. Schiele
ABSTRACT
Performance characterization of content-based image retrieval (CBIR) systems is especially difficult, because performance depends not only on the users, but also the tasks and the applications. In this paper, we propose a query-dependent performance characterization and optimization. The user specifies a high-level concept to be searched for, the size of the image region to be covered by the concept and an optimization constraint. Possible constraints might be 'maximum recall, 'maximum precision' or 'joint maximization of precision and recall'. The optimization proceeds in two stages. In the first stage, the detector best satisfying the user query is selected of a multitude of concept detectors. In the second stage, the information of the detectors is combined and optimized in order to reach optimum performance. Besides the optimization procedure itself the paper discusses the generation of multiple classifiers. In experiments, the advantage of jointly optimizing the query interval and the concept detector selection is shown. |
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