Approximating the Signature Quadratic Form Distance Using Scalable Feature Signatures

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F14%3A10281432" target="_blank" >RIV/00216208:11320/14:10281432 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007%2F978-3-319-04114-8_8" target="_blank" >http://link.springer.com/chapter/10.1007%2F978-3-319-04114-8_8</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-04114-8_8" target="_blank" >10.1007/978-3-319-04114-8_8</a>

Result language
angličtina
Original language name
Approximating the Signature Quadratic Form Distance Using Scalable Feature Signatures
Original language description
The feature signatures in connection with the signature quadratic form distance have become a respected similarity model for effective multimedia retrieval. However, the efficiency of the model is still a challenging task because the signature quadraticform distance has quadratic time complexity according to the number of tuples in feature signatures. In order to reduce the number of tuples in feature signatures, we introduce the scalable feature signatures, a new formal framework based on hierarchicalclustering enabling definition of various feature signature reduction techniques. As an example, we use the framework to define a new feature signature reduction technique based on joining of the tuples. We experimentally demonstrate our new feature signature reduction technique can be used to implement more efficient yet effective filter distances approximating the original signature quadratic form distance. We also show the filter distances using our new feature signature reduction te
Czech name
—
Czech description
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Project
<a href="/en/project/GPP202%2F12%2FP297" target="_blank" >GPP202/12/P297: Synergistic Modeling of Adaptive Similarities for Multimedia Retrieval</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
MultiMedia Modeling (Lecture Notes in Computer Science)
ISBN
978-3-319-04113-1
ISSN
0302-9743
e-ISSN
—
Number of pages
12
Pages from-to
86-97
Publisher name
Springer International Publishing
Place of publication
Berlin
Event location
Dublin, Ireland
Event date
Jan 6, 2014
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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