{"title":"帧率上转换的基于运动矢量的电影模式检测","authors":"S. Cho, S. Yoon, Young Hwan Kim","doi":"10.1109/ISOCC.2017.8368890","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel film mode detection method to improve the accuracy of frame rate up-conversion (FRUC). The existing methods need to calculate the field differences which are not necessary for FRUC. Furthermore, they prone to miss a non-film mode because they focus on detecting representative film modes, e.g., 3:2/2:2 pull-down. To avoid calculating field differences in film mode detection, the proposed method utilizes motion vectors which are already obtained from the FRUC. Furthermore, to improve the accuracy of detecting a non-film mode, the proposed method defines several features which use the variation of motion vectors for each frame. Then, it compares with the patterns of film modes. The proposed method can detect a non-film mode with 89.15% detection accuracy and increases the accuracy up to 10.93% for film modes compared to benchmark methods.","PeriodicalId":248826,"journal":{"name":"2017 International SoC Design Conference (ISOCC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Motion vector-based film mode detection for frame rate up-conversion\",\"authors\":\"S. Cho, S. Yoon, Young Hwan Kim\",\"doi\":\"10.1109/ISOCC.2017.8368890\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel film mode detection method to improve the accuracy of frame rate up-conversion (FRUC). The existing methods need to calculate the field differences which are not necessary for FRUC. Furthermore, they prone to miss a non-film mode because they focus on detecting representative film modes, e.g., 3:2/2:2 pull-down. To avoid calculating field differences in film mode detection, the proposed method utilizes motion vectors which are already obtained from the FRUC. Furthermore, to improve the accuracy of detecting a non-film mode, the proposed method defines several features which use the variation of motion vectors for each frame. Then, it compares with the patterns of film modes. The proposed method can detect a non-film mode with 89.15% detection accuracy and increases the accuracy up to 10.93% for film modes compared to benchmark methods.\",\"PeriodicalId\":248826,\"journal\":{\"name\":\"2017 International SoC Design Conference (ISOCC)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International SoC Design Conference (ISOCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISOCC.2017.8368890\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International SoC Design Conference (ISOCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISOCC.2017.8368890","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Motion vector-based film mode detection for frame rate up-conversion
This paper proposes a novel film mode detection method to improve the accuracy of frame rate up-conversion (FRUC). The existing methods need to calculate the field differences which are not necessary for FRUC. Furthermore, they prone to miss a non-film mode because they focus on detecting representative film modes, e.g., 3:2/2:2 pull-down. To avoid calculating field differences in film mode detection, the proposed method utilizes motion vectors which are already obtained from the FRUC. Furthermore, to improve the accuracy of detecting a non-film mode, the proposed method defines several features which use the variation of motion vectors for each frame. Then, it compares with the patterns of film modes. The proposed method can detect a non-film mode with 89.15% detection accuracy and increases the accuracy up to 10.93% for film modes compared to benchmark methods.