Naslov
Slow motion video sequences database for freezing artifact detection

Autori
Vrtar, Ela ; Herceg, Marijan ; Vranješ, Mario ; Babić, Danijel

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings IEEE ZINC 2023 / - Novi Sad, Srbija, 2023, 1-6

Skup
IEEE Zooming Innovation in Consumer Technology International Conference 2023 (ZINC 2023)

Mjesto i datum
Novi Sad, Srbija, 29.05.2023. - 31.05.2023

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
video freezing artifact ; no-reference algorithm ; video database

Sažetak
In this paper, a new video sequence database, called Slow Motion Video Sequences (SMVS), is developed. The developed SMVS database consists of 30 video sequences with very low temporal activities, where every sequence contains a freezing artifact. The performance of two freezing detection algorithms, the Histogram-Based Freezing Artifacts Detection Algorithm (HBFDA) and the Real-Time no-reference Freezing Detection Algorithm (RTFDA) are tested on the developed database. The testing results show the poor performance of the tested algorithms.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo

POVEZANOST RADA