{"title":"利用熵和SURF对视频进行场景分割","authors":"Junaid Baber, N. Afzulpurkar, Maheen Bakhtyar","doi":"10.1109/ICET.2011.6048496","DOIUrl":null,"url":null,"abstract":"In this paper we present a framework for video segmentation into scenes. Segmenting videos into scenes is the basic step for video analysis, efficient video indexing and content-based video retrieval. In our framework we used frame entropy and SURF descriptor to find shot boundaries from the videos. We extracted key frames from each shot and segmented the video into semantic scenes by key frame matching. The proposed algorithm gave promising results when applied to different genres of videos and dramas.","PeriodicalId":167049,"journal":{"name":"2011 7th International Conference on Emerging Technologies","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"16","resultStr":"{\"title\":\"Video segmentation into scenes using entropy and SURF\",\"authors\":\"Junaid Baber, N. Afzulpurkar, Maheen Bakhtyar\",\"doi\":\"10.1109/ICET.2011.6048496\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we present a framework for video segmentation into scenes. Segmenting videos into scenes is the basic step for video analysis, efficient video indexing and content-based video retrieval. In our framework we used frame entropy and SURF descriptor to find shot boundaries from the videos. We extracted key frames from each shot and segmented the video into semantic scenes by key frame matching. The proposed algorithm gave promising results when applied to different genres of videos and dramas.\",\"PeriodicalId\":167049,\"journal\":{\"name\":\"2011 7th International Conference on Emerging Technologies\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"16\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 7th International Conference on Emerging Technologies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICET.2011.6048496\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 7th International Conference on Emerging Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICET.2011.6048496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video segmentation into scenes using entropy and SURF
In this paper we present a framework for video segmentation into scenes. Segmenting videos into scenes is the basic step for video analysis, efficient video indexing and content-based video retrieval. In our framework we used frame entropy and SURF descriptor to find shot boundaries from the videos. We extracted key frames from each shot and segmented the video into semantic scenes by key frame matching. The proposed algorithm gave promising results when applied to different genres of videos and dramas.