Visual Image Search: Feature Signatures or/and Global Descriptors

This publication doesn't include Faculty of Arts. It includes Faculty of Informatics. Official publication website can be found on muni.cz.

Authors

LOKOČ Jakub NOVÁK David BATKO Michal SKOPAL Tomáš

Type Article in Proceedings
Conference Similarity Search and Applications
MU Faculty or unit

Faculty of Informatics

Citation
Web publisher site
Doi http://dx.doi.org/10.1007/978-3-642-32153-5_13
Field Informatics
Keywords similarity search; CBIR; global visual descriptors; visual signatures; SQFD
Attached files
Description The success of content-based retrieval systems stands or falls with the quality of the utilized similarity model. In the case of having no additional keywords or annotations provided with the multimedia data, the hard task is to guarantee the highest possible retrieval precision using only content-based retrieval techniques. In this paper we push the visual image search a step further by testing effective combination of two orthogonal approaches – the MPEG-7 global visual descriptors and the feature signatures equipped by the Signature Quadratic Form Distance. We investigate various ways of descriptor combinations and evaluate the overall effectiveness of the search on three different image collections. Moreover, we introduce a new image collection, TWIC, designed as a larger realistic image collection providing ground truth. In all the experiments, the combination of descriptors proved its superior performance on all tested collections. Furthermore, we propose a re-ranking variant guaranteeing efficient yet effective image retrieval.
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