19 May 2005 Image content engine (ICE): a system for fast image database searches
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Abstract
The Image Content Engine (ICE) is being developed to provide cueing assistance to human image analysts faced with increasingly large and intractable amounts of image data. The ICE architecture includes user configurable feature extraction pipelines which produce intermediate feature vector and match surface files which can then be accessed by interactive relational queries. Application of the feature extraction algorithms to large collections of images may be extremely time consuming and is launched as a batch job on a Linux cluster. The query interface accesses only the intermediate files and returns candidate hits nearly instantaneously. Queries may be posed for individual objects or collections. The query interface prompts the user for feedback, and applies relevance feedback algorithms to revise the feature vector weighting and focus on relevant search results. Examples of feature extraction and both model-based and search-by-example queries are presented.
© (2005) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
James M. Brase, James M. Brase, Douglas N. Poland, Douglas N. Poland, David W. Paglieroni, David W. Paglieroni, George F. Weinert, George F. Weinert, Charles W. Grant, Charles W. Grant, Aseneth S. Lopez, Aseneth S. Lopez, Sergei Nikolaev, Sergei Nikolaev, } "Image content engine (ICE): a system for fast image database searches", Proc. SPIE 5781, Optics and Photonics in Global Homeland Security, (19 May 2005); doi: 10.1117/12.608828; https://doi.org/10.1117/12.608828
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