bibtype J - Journal Article
ARLID 0518086
utime 20241106135802.3
mtime 20191217235959.9
SCOPUS 85074863872
WOS 000626525300003
DOI 10.1109/TPAMI.2019.2951664
title (primary) (eng) Affine Invariants of Vector Fields
specification
page_count 14 s.
media_type P
serial
ARLID cav_un_epca*0256725
ISSN 0162-8828
title IEEE Transactions on Pattern Analysis and Machine Intelligence
volume_id 43
volume 4 (2021)
page_num 1140-1155
publisher
name IEEE Computer Society
keyword Vector field
keyword total affine transformation
keyword affine invariants
author (primary)
ARLID cav_un_auth*0336802
name1 Kostková
name2 Jitka
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept (eng) Department of Image Processing
department (cz) ZOI
department (eng) ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101203
name1 Suk
name2 Tomáš
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101087
name1 Flusser
name2 Jan
institution UTIA-B
full_dept (cz) Zpracování obrazové informace
full_dept Department of Image Processing
department (cz) ZOI
department ZOI
full_dept Department of Image Processing
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
source_type PDF
url http://library.utia.cas.cz/separaty/2019/ZOI/kostkova-0518086.pdf
source
url https://ieeexplore.ieee.org/abstract/document/8892626
cas_special
project
project_id GA18-07247S
agency GA ČR
ARLID cav_un_auth*0360229
abstract (eng) Vector fields are a special kind of multidimensional data, which are in a certain sense similar to digital color images, but are distinct from them in several aspects. In each pixel, the field is assigned to a vector that shows the direction and the magnitude of the quantity, which has been measured. To detect the patterns of interest in the field, special matching methods must be developed. In this paper, we propose a method for the description and matching of vector field patterns under an unknown affine transformation of the field. Unlike digital images, transformations of vector fields act not only on the spatial coordinates but also on the field values, which makes the detection different from the image case. To measure the similarity between the template and the field patch, we propose original invariants with respect to total affine transformation. They are designed from the vector field moments. It is demonstrated by experiments on real data from fluid mechanics that they perform significantly better than potential competitors.
result_subspec WOS
RIV JD
FORD0 10000
FORD1 10200
FORD2 10201
reportyear 2022
num_of_auth 3
mrcbC52 4 A sml 4as 20241106135802.3
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0303983
confidential S
contract
name Copyright Receipt
date 20191102
mrcbC86 3+4 Article Computer Science Artificial Intelligence|Engineering Electrical Electronic
mrcbC91 C
mrcbT16-e COMPUTERSCIENCEARTIFICIALINTELLIGENCE|ENGINEERINGELECTRICALELECTRONIC
mrcbT16-j 6.752
mrcbT16-s 8.269
mrcbT16-D Q1*
mrcbT16-E Q1*
arlyear 2021
mrcbTft \nSoubory v repozitáři: kostkova-0518086-CopyrightReceipt.pdf
mrcbU14 85074863872 SCOPUS
mrcbU24 31714215 PUBMED
mrcbU34 000626525300003 WOS
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mrcbU63 cav_un_epca*0256725 IEEE Transactions on Pattern Analysis and Machine Intelligence 0162-8828 1939-3539 Roč. 43 č. 4 2021 1140 1155 IEEE Computer Society