0518086 20250310153227.820191217235959.9 85074863872 000626525300003 10.1109/TPAMI.2019.2951664 14 s. P cav_un_epca*02567250162-8828434 (2021)1140-1155IEEE Computer Society Vector field total affine transformation affine invariants cav_un_auth*0336802 Kostková Jitka UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101203 Suk Tomáš UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101087 Flusser Jan UTIA-B Zpracování obrazové informace Department of Image Processing ZOI ZOI Department of Image Processing Ústav teorie informace a automatizace AV ČR, v. v. i. PDF http://library.utia.cas.cz/separaty/2019/ZOI/kostkova-0518086.pdf https://ieeexplore.ieee.org/abstract/document/8892626 GA18-07247S GA ČR cav_un_auth*0360229 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. WOS JD 10000 10200 10201 2022 3 4 A sml 4as 2rh 20241106135802.3 2 R hod 20250310152145.5 20250310153227.8 RVO:67985556 http://hdl.handle.net/11104/0303983 S Copyright Receipt 20191102 3+4 Article Computer Science Artificial Intelligence|Engineering Electrical Electronic C ENGINEERING.ELECTRICAL&ELECTRONIC|COMPUTERSCIENCE.ARTIFICIALINTELLIGENCE 25.651 11.881 8.2 0.06631 6.752 73149 435 8.269 60.86 19.48 15519 Q1 24.000 312 Q1 99.2 Q1* Q1* 4.71 Q1 99.457 2021 Soubory v repozitáři: kostkova-0518086.pdf, kostkova-0518086-CopyrightReceipt.pdf 85074863872 SCOPUS 31714215 PUBMED 000626525300003 WOS PDF 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