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17 December 1998 Multimedia information retrieval by analyzing content and learning from examples
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Abstract
Multimedia information systems are experiencing a tremendous growth as a direct consequence of the popularity and pervasive use of the world wide web. As a consequence, it is becoming increasingly important to provide efficient and flexible solutions for accessing and retrieving multimedia data. Images and video are emerging as significant data types in multimedia systems. And yet, most commercial systems are still text and keyword based and do not fully exploit the image content of these systems. We believe that there is an opportunity to build a novel interactive multimedia system for some specific applications in electronic commerce. In this paper, we present an overview of our approach, the rationale behind it and the problems that are inherent in building such a system. We address some of the technical issues in representing and analyzing image primitive features. These are the building blocks of any such systems. They can be generalized into a much broader range of applications as well.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
S. Kicha Ganapathy, Zhibin Lei, and Robert J. Safranek "Multimedia information retrieval by analyzing content and learning from examples", Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); https://doi.org/10.1117/12.333895
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