Dynamic Texture Similarity Criterion
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21240%2F18%3A00321888" target="_blank" >RIV/68407700:21240/18:00321888 - isvavai.cz</a>
Result on the web
<a href="http://www.icpr2018.org/" target="_blank" >http://www.icpr2018.org/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICPR.2018.8545370" target="_blank" >10.1109/ICPR.2018.8545370</a>
Alternative languages
Result language
angličtina
Original language name
Dynamic Texture Similarity Criterion
Original language description
Evaluating the likeness of two similar dynamic textures or dynamic textures of the same type is still a challenging and unresolved problem. Temporal dimension and dynamics in texture complicates the problem of mere texture similarities and makes it even more challenging. A simple approach to compute difference between DTs bag of features, STSIM of pure statistisc methods are insufficient and does not affect the variable texture dynamics which is crucial for human recognition. Testing the similarity, quality and fidelity of both natural and arftificial dynamic textures is a problem that can be solved by psychometric tests with users, but these are challenging both in terms of time, human resources and data processing. The solution provided by us compares the frequency and regularity of the time behavior of spatial frequencies in texture with great consistency with the values provided by users testing. The solution itself provides a functional metric that can be used to evaluate the similarity of textures modified by inpainting, retouching as well as evaluating the similarity of the dynamics across the type of the DTs.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2018 24rd International Conference on Pattern Recognition (ICPR)
ISBN
978-1-5386-3788-3
ISSN
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e-ISSN
1051-4651
Number of pages
6
Pages from-to
904-909
Publisher name
IEEE
Place of publication
Piscataway, NJ
Event location
Beijing
Event date
Aug 20, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000455146800151