{"title":"4种密集精确深度恢复算法的定量比较","authors":"Baozhong Tian, J. Barron","doi":"10.1109/CRV.2005.11","DOIUrl":null,"url":null,"abstract":"We report on four algorithms for recovering dense depth maps from long image sequences, where the camera motion is known a priori. All methods use a Kalman filter to integrate intensity derivatives or optical flow over time to increase accuracy.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A quantitative comparison of 4 algorithms for recovering dense accurate depth\",\"authors\":\"Baozhong Tian, J. Barron\",\"doi\":\"10.1109/CRV.2005.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We report on four algorithms for recovering dense depth maps from long image sequences, where the camera motion is known a priori. All methods use a Kalman filter to integrate intensity derivatives or optical flow over time to increase accuracy.\",\"PeriodicalId\":307318,\"journal\":{\"name\":\"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CRV.2005.11\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CRV.2005.11","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A quantitative comparison of 4 algorithms for recovering dense accurate depth
We report on four algorithms for recovering dense depth maps from long image sequences, where the camera motion is known a priori. All methods use a Kalman filter to integrate intensity derivatives or optical flow over time to increase accuracy.
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