{"title":"Slow motion video sequences database for freezing artifact detection","authors":"Ela Vrtar, M. Herceg, M. Vranješ, Danijel Babic","doi":"10.1109/ZINC58345.2023.10174092","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":383771,"journal":{"name":"2023 Zooming Innovation in Consumer Technologies Conference (ZINC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 Zooming Innovation in Consumer Technologies Conference (ZINC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ZINC58345.2023.10174092","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract
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.
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