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10 January 2003 Semantic image browsing using hidden categories and confidence values
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Abstract
In this paper we propose a photo browsing system that uses image classification results in an error tolerant manner. Images are hierarchically classified into indoor/outdoor and further into city/landscape. We employ simple classifiers based on global color histogram, wavelet subband energies and contour directions having medium recall rates around 85%. This paper delivers two contributions to cope with classification errors in the context of image browsing. The first contribution is a method to associate confidence measures to classification results. A second contribution is a browsing tool that does not reveal classification results to the user. Instead, browsing options are generated. These browsing options are thumbnails representing semantic topics such as indoor and outdoor. User studies showed that thumbnails and semantic topics are highly demanded features for a photo-browsing tool. The thumbnails are representative images from the database with high confidence values. The thumbnails are chosen context-based such that they have class labels in common with currently displayed images or usage history.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juergen Stauder, Gael Gouzien, Bertrand Chupeau, Loic Nunez, Jean-Ronan Vigouroux, and Ewa Kijak "Semantic image browsing using hidden categories and confidence values", Proc. SPIE 5021, Storage and Retrieval for Media Databases 2003, (10 January 2003); https://doi.org/10.1117/12.476260
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