Matthias Grundmann, Vivek Kwatra, Daniel Castro, Irfan Essa
{"title":"无需校准的卷帘门拆卸","authors":"Matthias Grundmann, Vivek Kwatra, Daniel Castro, Irfan Essa","doi":"10.1109/ICCPhot.2012.6215213","DOIUrl":null,"url":null,"abstract":"We present a novel algorithm for efficient removal of rolling shutter distortions in uncalibrated streaming videos. Our proposed method is calibration free as it does not need any knowledge of the camera used, nor does it require calibration using specially recorded calibration sequences. Our algorithm can perform rolling shutter removal under varying focal lengths, as in videos from CMOS cameras equipped with an optical zoom. We evaluate our approach across a broad range of cameras and video sequences demonstrating robustness, scaleability, and repeatability. We also conducted a user study, which demonstrates preference for the output of our algorithm over other state-of-the art methods. Our algorithm is computationally efficient, easy to parallelize, and robust to challenging artifacts introduced by various cameras with differing technologies.","PeriodicalId":169984,"journal":{"name":"2012 IEEE International Conference on Computational Photography (ICCP)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"177","resultStr":"{\"title\":\"Calibration-free rolling shutter removal\",\"authors\":\"Matthias Grundmann, Vivek Kwatra, Daniel Castro, Irfan Essa\",\"doi\":\"10.1109/ICCPhot.2012.6215213\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present a novel algorithm for efficient removal of rolling shutter distortions in uncalibrated streaming videos. Our proposed method is calibration free as it does not need any knowledge of the camera used, nor does it require calibration using specially recorded calibration sequences. Our algorithm can perform rolling shutter removal under varying focal lengths, as in videos from CMOS cameras equipped with an optical zoom. We evaluate our approach across a broad range of cameras and video sequences demonstrating robustness, scaleability, and repeatability. We also conducted a user study, which demonstrates preference for the output of our algorithm over other state-of-the art methods. Our algorithm is computationally efficient, easy to parallelize, and robust to challenging artifacts introduced by various cameras with differing technologies.\",\"PeriodicalId\":169984,\"journal\":{\"name\":\"2012 IEEE International Conference on Computational Photography (ICCP)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-04-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"177\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE International Conference on Computational Photography (ICCP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPhot.2012.6215213\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE International Conference on Computational Photography (ICCP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPhot.2012.6215213","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
We present a novel algorithm for efficient removal of rolling shutter distortions in uncalibrated streaming videos. Our proposed method is calibration free as it does not need any knowledge of the camera used, nor does it require calibration using specially recorded calibration sequences. Our algorithm can perform rolling shutter removal under varying focal lengths, as in videos from CMOS cameras equipped with an optical zoom. We evaluate our approach across a broad range of cameras and video sequences demonstrating robustness, scaleability, and repeatability. We also conducted a user study, which demonstrates preference for the output of our algorithm over other state-of-the art methods. Our algorithm is computationally efficient, easy to parallelize, and robust to challenging artifacts introduced by various cameras with differing technologies.