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@inproceedings{990923,
author = {Lokoč, Jakub and Novák, David and Batko, Michal and Skopal, Tomáš},
address = {Berlin / Heidelberg},
booktitle = {Similarity Search and Applications},
doi = {http://dx.doi.org/10.1007/978-3-642-32153-5_13},
editor = {Navarro, Gonzalo and Pestov, Vladimir},
keywords = {similarity search; CBIR; global visual descriptors; visual signatures; SQFD},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Berlin / Heidelberg},
isbn = {978-3-642-32152-8},
pages = {177-191},
publisher = {Springer},
title = {Visual Image Search: Feature Signatures or/and Global Descriptors},
url = {http://www.springerlink.com/content/g61n208277656084/},
year = {2012}
}
TY - JOUR
ID - 990923
AU - Lokoč, Jakub - Novák, David - Batko, Michal - Skopal, Tomáš
PY - 2012
TI - Visual Image Search: Feature Signatures or/and Global Descriptors
PB - Springer
CY - Berlin / Heidelberg
SN - 9783642321528
KW - similarity search
KW - CBIR
KW - global visual descriptors
KW - visual signatures
KW - SQFD
UR - http://www.springerlink.com/content/g61n208277656084/
L2 - http://www.springerlink.com/content/g61n208277656084/
N2 - 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.
ER -
LOKOČ, Jakub, David NOVÁK, Michal BATKO a Tomáš SKOPAL. Visual Image Search: Feature Signatures or/and Global Descriptors. In Navarro, Gonzalo and Pestov, Vladimir. \textit{Similarity Search and Applications}. Berlin / Heidelberg: Springer, 2012, s.~177-191. ISBN~978-3-642-32152-8. Dostupné z: https://dx.doi.org/10.1007/978-3-642-32153-5\_{}13.
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