{"title":"混合摄像机网络的标定","authors":"Xilin Chen, Jie Yang, A. Waibel","doi":"10.1109/ICCV.2003.1238330","DOIUrl":null,"url":null,"abstract":"Visual surveillance using a camera network has imposed new challenges to camera calibration. An essential problem is that a large number of cameras may not have a common field of view or even be synchronized well. We propose to use a hybrid camera network that consists of catadioptric and perspective cameras for a visual surveillance task. The relations between multiple views of a scene captured from different cameras can be then calibrated under the catadioptric camera's coordinate system. We address the important issue of how to calibrate the hybrid camera network. We calibrate the hybrid camera network in three steps. First, we calibrate the catadioptric camera using only the vanishing points. In order to reduce computational complexity, we calibrate the camera without the mirror first and then calibrate the catadioptric camera system. Second, we determine 3D positions of some points using as few as two spatial parallel lines and some equidistance points. Finally, we calibrate other perspective cameras based on these known spatial points.","PeriodicalId":131580,"journal":{"name":"Proceedings Ninth IEEE International Conference on Computer Vision","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2003-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"40","resultStr":"{\"title\":\"Calibration of a hybrid camera network\",\"authors\":\"Xilin Chen, Jie Yang, A. Waibel\",\"doi\":\"10.1109/ICCV.2003.1238330\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Visual surveillance using a camera network has imposed new challenges to camera calibration. An essential problem is that a large number of cameras may not have a common field of view or even be synchronized well. We propose to use a hybrid camera network that consists of catadioptric and perspective cameras for a visual surveillance task. The relations between multiple views of a scene captured from different cameras can be then calibrated under the catadioptric camera's coordinate system. We address the important issue of how to calibrate the hybrid camera network. We calibrate the hybrid camera network in three steps. First, we calibrate the catadioptric camera using only the vanishing points. In order to reduce computational complexity, we calibrate the camera without the mirror first and then calibrate the catadioptric camera system. Second, we determine 3D positions of some points using as few as two spatial parallel lines and some equidistance points. Finally, we calibrate other perspective cameras based on these known spatial points.\",\"PeriodicalId\":131580,\"journal\":{\"name\":\"Proceedings Ninth IEEE International Conference on Computer Vision\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2003-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"40\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings Ninth IEEE International Conference on Computer Vision\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCV.2003.1238330\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings Ninth IEEE International Conference on Computer Vision","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCV.2003.1238330","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Visual surveillance using a camera network has imposed new challenges to camera calibration. An essential problem is that a large number of cameras may not have a common field of view or even be synchronized well. We propose to use a hybrid camera network that consists of catadioptric and perspective cameras for a visual surveillance task. The relations between multiple views of a scene captured from different cameras can be then calibrated under the catadioptric camera's coordinate system. We address the important issue of how to calibrate the hybrid camera network. We calibrate the hybrid camera network in three steps. First, we calibrate the catadioptric camera using only the vanishing points. In order to reduce computational complexity, we calibrate the camera without the mirror first and then calibrate the catadioptric camera system. Second, we determine 3D positions of some points using as few as two spatial parallel lines and some equidistance points. Finally, we calibrate other perspective cameras based on these known spatial points.