{"title":"静态摄像机监控视频中帧移除检测方法","authors":"A. Bavrina","doi":"10.1109/ITNT57377.2023.10139053","DOIUrl":null,"url":null,"abstract":"A method is proposed for passive protection of a surveillance camera video from a video fragment deletion attack. The method is based on the construction of local features for the samples of two consecutive frames, followed by a multilayer neural network classification. Post-processing and calculation of statistics based on the results of the classification make it possible to decide whether a given pair of frames is sequential or a number of frames were cut between them. Experiments show the efficiency of detecting the fact of a fragment removal even from stationary scenes, when such a deletion is visually imperceptible.","PeriodicalId":296438,"journal":{"name":"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Method for Frame Removal Detection in Static Camera Surveillance Video\",\"authors\":\"A. Bavrina\",\"doi\":\"10.1109/ITNT57377.2023.10139053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method is proposed for passive protection of a surveillance camera video from a video fragment deletion attack. The method is based on the construction of local features for the samples of two consecutive frames, followed by a multilayer neural network classification. Post-processing and calculation of statistics based on the results of the classification make it possible to decide whether a given pair of frames is sequential or a number of frames were cut between them. Experiments show the efficiency of detecting the fact of a fragment removal even from stationary scenes, when such a deletion is visually imperceptible.\",\"PeriodicalId\":296438,\"journal\":{\"name\":\"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ITNT57377.2023.10139053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IX International Conference on Information Technology and Nanotechnology (ITNT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITNT57377.2023.10139053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Method for Frame Removal Detection in Static Camera Surveillance Video
A method is proposed for passive protection of a surveillance camera video from a video fragment deletion attack. The method is based on the construction of local features for the samples of two consecutive frames, followed by a multilayer neural network classification. Post-processing and calculation of statistics based on the results of the classification make it possible to decide whether a given pair of frames is sequential or a number of frames were cut between them. Experiments show the efficiency of detecting the fact of a fragment removal even from stationary scenes, when such a deletion is visually imperceptible.