Content Management White Papers
Automated Benchmarking in Content-Based Image Retrieval
Overview Benchmarking has always been a crucial problem in content-based image retrieval (CBIR). A key issue is the lack of a common access method to retrieval systems, such as SQL for relational databases. The Multimedia Retrieval Mark-up Language (MRML) solves this problem by standardizing access to CBIR systems (CBIRSs). Other difficult problems are also shortly addressed, such as obtaining relevance judgments and choosing a database for performance comparison. In this article we present a fully automated benchmark for CBIRSs based on MRML, which can be adapted to any image database and almost any kind of relevance judgment. The test evaluates the performance of positive and negative relevance feedback, which can be generated automatically from the relevance judgments.
| Publisher | University of Geneva | File Format | PDF, requires Acrobat Rdr 5 |
|---|---|---|---|
| Date Published | January 2001 | Downloads | 9 |
| Format | White Papers | ||
| Topics | |||
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