{"title":"基于多尺度相位局部特征的关键帧提取","authors":"Lin Honghua, Yang Xuan, Pei Jihong","doi":"10.1109/ICOSP.2008.4697304","DOIUrl":null,"url":null,"abstract":"Key-frames are representative frames in a shot. Key frame extraction is one of the basic procedures relating to video retrieval and indexing. In view of the surveillance video characteristic and the user attention focus, this paper proposed a key frame extraction method based on multi-scale phase-based local features. Prior to key frame extraction, the video should be segmented into shots. Then, find the interest points in the head of the moving target extracted by adaptive background mixture Gaussian models, mark the candidate key frame which has a certain number of interest points matching with the given target model. Lastly, for each shot, extract key frame which has the best similar match. Experimental results demonstrate that the proposed method is feasible and effective.","PeriodicalId":445699,"journal":{"name":"2008 9th International Conference on Signal Processing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Key frame extraction based on multi-scale phase-based local features\",\"authors\":\"Lin Honghua, Yang Xuan, Pei Jihong\",\"doi\":\"10.1109/ICOSP.2008.4697304\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Key-frames are representative frames in a shot. Key frame extraction is one of the basic procedures relating to video retrieval and indexing. In view of the surveillance video characteristic and the user attention focus, this paper proposed a key frame extraction method based on multi-scale phase-based local features. Prior to key frame extraction, the video should be segmented into shots. Then, find the interest points in the head of the moving target extracted by adaptive background mixture Gaussian models, mark the candidate key frame which has a certain number of interest points matching with the given target model. Lastly, for each shot, extract key frame which has the best similar match. Experimental results demonstrate that the proposed method is feasible and effective.\",\"PeriodicalId\":445699,\"journal\":{\"name\":\"2008 9th International Conference on Signal Processing\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-12-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 9th International Conference on Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2008.4697304\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 9th International Conference on Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2008.4697304","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Key frame extraction based on multi-scale phase-based local features
Key-frames are representative frames in a shot. Key frame extraction is one of the basic procedures relating to video retrieval and indexing. In view of the surveillance video characteristic and the user attention focus, this paper proposed a key frame extraction method based on multi-scale phase-based local features. Prior to key frame extraction, the video should be segmented into shots. Then, find the interest points in the head of the moving target extracted by adaptive background mixture Gaussian models, mark the candidate key frame which has a certain number of interest points matching with the given target model. Lastly, for each shot, extract key frame which has the best similar match. Experimental results demonstrate that the proposed method is feasible and effective.