CoPhIR Image Collection under the Microscope
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F09%3A00029662" target="_blank" >RIV/00216224:14330/09:00029662 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
CoPhIR Image Collection under the Microscope
Original language description
The Content-based Photo Image Retrieval (CoPhIR) dataset is the largest available database of digital images with corresponding visual descriptors. It contains five MPEG-7 global descriptors extracted from more than 106 million images from Flickr photo-sharing system. In this paper, we analyze this dataset focusing on 1) efficiency of similarity-based indexing and searching and on 2) expressiveness of combination of the descriptors with respect to subjective perception of visual similarity. We treat thedescriptors as metric spaces and then combine them into a multi-metric space. We analyze distance distributions of individual descriptors, measure intrinsic dimensionality of these datasets and statistically evaluate correlation between these descriptors. Further, we use two methods to assess subjective accuracy and satisfaction of similarity retrieval based on a combination of descriptors that is recommended for CoPhIR, and we compare these results on databases of 10 and 100 million Co
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA201%2F09%2F0683" target="_blank" >GA201/09/0683: Similarity searching in very large multimedia databases</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 2009 Second International Workshop on Similarity Search and Applications
ISBN
978-0-7695-3765-8
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
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Publisher name
IEEE Computer Society
Place of publication
Washington, DC, USA
Event location
Prague, Czech Republic
Event date
Jan 1, 2009
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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