Sketch-Based Image Retrieval: Benchmark and Bag-of-Features Descriptors

We introduce a benchmark for evaluating the performance of large-scale sketch-based image retrieval systems. The necessary data are acquired in a controlled user study where subjects rate how well given sketch/image pairs match. We suggest how to use the data for evaluating the performance of sketch...

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Bibliographic Details
Published inIEEE transactions on visualization and computer graphics Vol. 17; no. 11; pp. 1624 - 1636
Main Authors Eitz, M., Hildebrand, K., Boubekeur, T., Alexa, M.
Format Journal Article
LanguageEnglish
Published United States IEEE 01.11.2011
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Institute of Electrical and Electronics Engineers
Subjects
Benchmark testing
Benchmarking
Computer graphics
Computer Science
Correlation
Humans
image databases
Image Processing
Image retrieval
Image/video retrieval
Performance evaluation
Retrieval
Shape
Sketches
Visualization
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Summary:We introduce a benchmark for evaluating the performance of large-scale sketch-based image retrieval systems. The necessary data are acquired in a controlled user study where subjects rate how well given sketch/image pairs match. We suggest how to use the data for evaluating the performance of sketch-based image retrieval systems. The benchmark data as well as the large image database are made publicly available for further studies of this type. Furthermore, we develop new descriptors based on the bag-of-features approach and use the benchmark to demonstrate that they significantly outperform other descriptors in the literature.
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ISSN:1077-2626
1941-0506
1941-0506
DOI:10.1109/TVCG.2010.266