On Effects of Visual Query Complexity

As an effective technique to manage large scale image collections, content-based image retrieval (CBIR) has been received great attentions and became a very active research domain in recent years. While assessing system performance is one of the key factors for the related technological advancement, relatively little attention has been paid to model and analyze test queries. This paper documents a study on the problem of determining “visual query complexity” as a measure for predicting image retrieval performance. We propose a quantitative metric for measuring complexity of image queries for content-based image search engine. A set of experiments are carried out using IAPR TC-12 Benchmark. The results demonstrate the effectiveness of the measurement, and verify that the retrieval accuracy of a query is inversely associated with the complexity level of its visual content.

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