Materials Classification using Sparse Gray-Scale Bidirectional Reflectance Measurements
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F15%3A00447072" target="_blank" >RIV/67985556:_____/15:00447072 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-319-23117-4_25" target="_blank" >http://dx.doi.org/10.1007/978-3-319-23117-4_25</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-23117-4_25" target="_blank" >10.1007/978-3-319-23117-4_25</a>
Alternative languages
Result language
angličtina
Original language name
Materials Classification using Sparse Gray-Scale Bidirectional Reflectance Measurements
Original language description
Material recognition applications use typically color texture-based features; however, the underlying measurements are in several application fields unavailable or too expensive. Therefore, bidirectional reflectance measurements are used, i.e., dependenton both illumination and viewing directions. But even measurement of such BRDF data is very time- and resources-demanding. In this paper we use dependency-aware feature selection method to identify very sparse set of the most discriminative bidirectional reflectance samples that can reliably distinguish between three types of materials from BRDF database - fabric, wood, and leather. We conclude that ten gray-scale samples primarily at high illumination and viewing elevations are sufficient to identifytype of material with accuracy over 96/%. We analyze estimated placement of the bidirectional samples for discrimination between different types of materials. The stability of such directional samples is very high as was verified by an ad
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BD - Information theory
OECD FORD branch
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Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2015
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Computer Analysis of Images and Patterns - CAIP 2015
ISBN
978-3-319-23192-1
ISSN
0302-9743
e-ISSN
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Number of pages
11
Pages from-to
289-299
Publisher name
Springer International Publishing
Place of publication
Switzerland
Event location
Valletta
Event date
Sep 2, 2015
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000364694000025