{"title":"Identification of Interpolated Frames by Motion-Compensated Frame-Interpolation via Measuring Irregularity of Optical Flow","authors":"Xiangling Ding, Yanming Huang, Dengyong Zhang, Junlin Ouyang","doi":"10.4018/ijdcf.295813","DOIUrl":null,"url":null,"abstract":"Motion-compensated frame-interpolation (MCFI), synthesize intermediate frames between input frames guided by estimated motion, can be employed to falsify high bit-rate videos or high frame-rate videos with different frame-rates. Although existing MCFI identification methods have obtained satisfactory results, they are seriously degraded by stronger compression. Therefore, to conquer this issue, a blind forensics method is proposed to identify the adopted MCFI methods by considering the irregularities of optical flow produced by various MCFIs. In this paper, a set of compact features are constructed from the motion-aligned frame difference-weighted histogram of local binary pattern on the basis of optical flow (MAFD-WHLBP). Experimental results show that the proposed approach outperforms existing MCFI detectors under stronger compression.","PeriodicalId":44650,"journal":{"name":"International Journal of Digital Crime and Forensics","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2021-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Digital Crime and Forensics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijdcf.295813","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Motion-compensated frame-interpolation (MCFI), synthesize intermediate frames between input frames guided by estimated motion, can be employed to falsify high bit-rate videos or high frame-rate videos with different frame-rates. Although existing MCFI identification methods have obtained satisfactory results, they are seriously degraded by stronger compression. Therefore, to conquer this issue, a blind forensics method is proposed to identify the adopted MCFI methods by considering the irregularities of optical flow produced by various MCFIs. In this paper, a set of compact features are constructed from the motion-aligned frame difference-weighted histogram of local binary pattern on the basis of optical flow (MAFD-WHLBP). Experimental results show that the proposed approach outperforms existing MCFI detectors under stronger compression.