0492503 20240103220354.320180827235959.9 85059755327 000455146800151 10.1109/ICPR.2018.8545370 6 s. P cav_un_epca*0492502978-1-5386-3787-6904-909New YorkIEEE2018 Dynamic texture Similarity criterion cav_un_auth*0295135 Richtr Radek Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition CZ Ústav teorie informace a automatizace AV ČR, v. v. i. cav_un_auth*0101093 Haindl Michal Rozpoznávání obrazu Department of Pattern Recognition RO RO UTIA-B Department of Pattern Recognition Ústav teorie informace a automatizace AV ČR, v. v. i. http://library.utia.cas.cz/separaty/2018/RO/haindl-0492503.pdf Dynamic texture similarity ranking is a challenging and still unsolved problem. Evaluation of how well are various dynamic textures similar to humans perception viewis extremely difficult even for static textures and requires tedious psycho-physical experiments. Human perception principles are largely not understood yet and the dynamic texture perception is further complicated with a distinct way of perceiving spatial and temporal domains, which complicates any similarity criterion definition. We propose a novel dynamic texture criterion based on the Fourier transformation and properties of dynamic texture spatiotemporal frequencies. The presented criterion correlates well with performed psycho-physical tests while maintaining sufficient diversity and descriptiveness. cav_un_auth*0363310 The 24th International Conference on Pattern Recognition (ICPR 2018) 20180820 20180824 Beijing CN BD 20000 20200 20205 2019 2 PO RVO:67985556 http://hdl.handle.net/11104/0286555 S 3+4 Proceedings Paper Computer Science Artificial Intelligence 2018 85059755327 SCOPUS PUBMED 000455146800151 WOS cav_un_epca*0492502 The 24th International Conference on Pattern Recognition (ICPR 2018) 978-1-5386-3787-6 904 909 New York IEEE 2018