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Performance Evaluation in Content-Based Image Retrieval: Overview and Proposals
Tipo de publicação: Artigo
Citação: MMS2000d
Journal: Pattern Recognition Letters
Volume: 22
Número: 5
Ano: 2001
Mês: april
Páginas: 593-601
Nota: Special Issue on Image and Video Indexing
Resumo: Evaluation of retrieval performance is a crucial problem in content-based image retrieval (CBIR). Many different methods for measuring the performance of a system have been created and used by researchers. This article discusses the advantages and shortcomings of the performance measures currently used. Problems such as defining a common image database for performance comparisons and a means of getting relevance judgments (or ground truth) for queries are explained. The relationship between CBIR and information retrieval (IR) is made clear, since IR researchers have decades of experience with the evaluation problem. Many of their solutions can be used for CBIR, despite the differences between the fields. Several methods used in text retrieval are explained. Proposals for performance measures and means of developing a standard test suite for CBIR, similar to that used in IR at the annual Text REtrieval Conference (TREC), are presented.
Campos do usuário: vgproject={viper}, vgclass={refpap},
Palavras-chave: Benchmarking, image retrieval, information retrieval evaluation, Medical image analysis and retrieval, performance evaluation
Autores Müller, Henning
Müller, Wolfgang
Squire, David McG.
Marchand-Maillet, Stéphane
Pun, Thierry
Editores Bunke, Horst
Jiang, X.
Adicionado por: []
Total mark: 0
Anexos
  • MMS2000d.pdf
Notas
    Tópicos