{"title":"视频数据库中幻灯片检测的鲁棒平移分析","authors":"Zbigniew Zdziarski, Rozenn Dahyot","doi":"10.1109/IMVIP.2009.23","DOIUrl":null,"url":null,"abstract":"We present an algorithm for slideshow detection in video databases such as YouTube or Blip.TV. Our solution is based around feature tracking to extract movement between sequentially captured frames. This movement is then analysed through the use of the Hough Transform and compared against behaviour commonly exhibited by slideshows: still and panning static images. We show experimentally the effectiveness of this novel idea and approach.","PeriodicalId":179564,"journal":{"name":"2009 13th International Machine Vision and Image Processing Conference","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2009-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Robust Panning Analysis for Slideshow Detection in Video Databases\",\"authors\":\"Zbigniew Zdziarski, Rozenn Dahyot\",\"doi\":\"10.1109/IMVIP.2009.23\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present an algorithm for slideshow detection in video databases such as YouTube or Blip.TV. Our solution is based around feature tracking to extract movement between sequentially captured frames. This movement is then analysed through the use of the Hough Transform and compared against behaviour commonly exhibited by slideshows: still and panning static images. We show experimentally the effectiveness of this novel idea and approach.\",\"PeriodicalId\":179564,\"journal\":{\"name\":\"2009 13th International Machine Vision and Image Processing Conference\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 13th International Machine Vision and Image Processing Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IMVIP.2009.23\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 13th International Machine Vision and Image Processing Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMVIP.2009.23","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Robust Panning Analysis for Slideshow Detection in Video Databases
We present an algorithm for slideshow detection in video databases such as YouTube or Blip.TV. Our solution is based around feature tracking to extract movement between sequentially captured frames. This movement is then analysed through the use of the Hough Transform and compared against behaviour commonly exhibited by slideshows: still and panning static images. We show experimentally the effectiveness of this novel idea and approach.