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Efficiently support concurrent queries in multiuser CBIR systems

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Abstract

Various techniques have been developed for different query types in content-based image retrieval systems such as sampling queries, constrained sampling queries, multiple constrained sampling queries, k-NN queries, constrained k-NN queries, and multiple localized k-NN queries. In this paper, we propose a generalized query model suitable for expressing queries of different types, and investigate efficient processing techniques for this new framework. We exploit sequential access and data sharing by developing new storage and query processing techniques to leverage inter-query concurrency. Our experimental results, based on the Corel dataset, indicate that the proposed optimization can significantly reduce average response time in a multiuser environment, and achieve better retrieval precision and recall compared to two recent techniques.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Central Florida, Orlando, FL, 32816, USA

    Danzhou Liu, Kien A. Hua & Ning Yu

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  1. Danzhou Liu
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  2. Kien A. Hua
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  3. Ning Yu
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Correspondence to Danzhou Liu.

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Liu, D., Hua, K.A. & Yu, N. Efficiently support concurrent queries in multiuser CBIR systems. Multimed Tools Appl 42, 273–293 (2009). https://doi.org/10.1007/s11042-008-0244-x

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