| bibtype |
C -
Conference Paper (international conference)
|
| ARLID |
0510488 |
| utime |
20240103222838.1 |
| mtime |
20191106235959.9 |
| SCOPUS |
85076168125 |
| WOS |
000582481300012 |
| DOI |
10.1007/978-3-030-33720-9_12 |
| title
(primary) (eng) |
View Dependent Surface Material Recognition |
| specification |
| page_count |
12 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0510482 |
| ISBN |
978-3-030-33719-3 |
| ISSN |
0302-9743 |
| title
|
Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019) |
| page_num |
156-167 |
| publisher |
| place |
Cham |
| name |
Springer |
| year |
2019 |
|
| editor |
|
| editor |
|
| editor |
|
| editor |
|
|
| keyword |
convolutional neural network |
| keyword |
texture recognition |
| keyword |
Bidirectional Texture Function recognition |
| author
(primary) |
| ARLID |
cav_un_auth*0101165 |
| name1 |
Mikeš |
| name2 |
Stanislav |
| institution |
UTIA-B |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept (eng) |
Department of Pattern Recognition |
| department (cz) |
RO |
| department (eng) |
RO |
| full_dept |
Department of Pattern Recognition |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0101093 |
| name1 |
Haindl |
| name2 |
Michal |
| institution |
UTIA-B |
| full_dept (cz) |
Rozpoznávání obrazu |
| full_dept |
Department of Pattern Recognition |
| department (cz) |
RO |
| department |
RO |
| full_dept |
Department of Pattern Recognition |
| garant |
K |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| source |
|
| cas_special |
| project |
| project_id |
GA19-12340S |
| agency |
GA ČR |
| country |
CZ |
| ARLID |
cav_un_auth*0376011 |
|
| abstract
(eng) |
The paper presents a detailed study of surface material recognition dependence on the illumination and viewing conditions which is a hard challenge in a realistic scene interpretation. The results document sharp classification accuracy decrease when using usual texture recognition approach, i.e., small learning set size and the vertical viewing and illumination angle which is a very inadequate representation of the enormous material appearance variability. The visual appearance of materials is considered in the state-of-the-art Bidirectional Texture Function (BTF) representation and measured using the upper-end BTF gonioreflectometer. The materials in this study are sixty-five different wood species. The supervised material recognition uses the shallow convolutional neural network (CNN) for the error analysis of angular dependency. We propose a Gaussian mixture model-based method for robust material segmentation. |
| action |
| ARLID |
cav_un_auth*0382047 |
| name |
International Symposium on Visual Computing (ISVC 2019) /14./ |
| dates |
20191007 |
| mrcbC20-s |
20191009 |
| place |
Lake Tahoe |
| country |
US |
|
| RIV |
BD |
| FORD0 |
20000 |
| FORD1 |
20200 |
| FORD2 |
20205 |
| reportyear |
2020 |
| num_of_auth |
2 |
| mrcbC52 |
4 A sml 4as 20231122144408.5 |
| presentation_type |
PR |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0302678 |
| confidential |
S |
| contract |
| name |
Contract Book Contributor Consent to Publish |
| date |
20190904 |
|
| article_num |
12 |
| arlyear |
2019 |
| mrcbTft |
\nSoubory v repozitáři: haindl-0510488-Contract_Book_Contributor_Consent_to_Publish_LNCS_SIP_MH.pdf |
| mrcbU14 |
85076168125 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000582481300012 WOS |
| mrcbU63 |
cav_un_epca*0510482 Advances in Visual Computing : 14th International Symposium on Visual Computing (ISVC 2019) 978-3-030-33719-3 0302-9743 1611-3349 156 167 Cham Springer 2019 Lecture Notes in Computer Science 11844 |
| mrcbU67 |
340 Bebis G. |
| mrcbU67 |
340 Boyle R. |
| mrcbU67 |
340 Parvin B. |
| mrcbU67 |
340 Koracin D. |
|