{"title":"稀疏距离信息的场景重建","authors":"Guangyi Chen, G. Dudek, L. Torres-Méndez","doi":"10.1109/CRV.2005.70","DOIUrl":null,"url":null,"abstract":"This paper addresses an approach to scene reconstruction by inferring missing range data in a partial range map based on intensity image and sparse initial range data. It is assumed that the initial known range data is given on a number of scan lines one pixel width. This assumption is natural for a range sensor to acquire range data in a 3D real world environment. Both edge information of the intensity image and linear interpolation of the range data are used. Experiments show that this method gives very good results in inferring missing range data. It outperforms both the previous method and bilinear interpolation when a very small percentage of range data is known.","PeriodicalId":307318,"journal":{"name":"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Scene reconstruction with sparse range information\",\"authors\":\"Guangyi Chen, G. Dudek, L. Torres-Méndez\",\"doi\":\"10.1109/CRV.2005.70\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper addresses an approach to scene reconstruction by inferring missing range data in a partial range map based on intensity image and sparse initial range data. It is assumed that the initial known range data is given on a number of scan lines one pixel width. This assumption is natural for a range sensor to acquire range data in a 3D real world environment. Both edge information of the intensity image and linear interpolation of the range data are used. Experiments show that this method gives very good results in inferring missing range data. It outperforms both the previous method and bilinear interpolation when a very small percentage of range data is known.\",\"PeriodicalId\":307318,\"journal\":{\"name\":\"The 2nd Canadian Conference on Computer and Robot Vision (CRV'05)\",\"volume\":\"21 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.2005.70\",\"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.2005.70","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scene reconstruction with sparse range information
This paper addresses an approach to scene reconstruction by inferring missing range data in a partial range map based on intensity image and sparse initial range data. It is assumed that the initial known range data is given on a number of scan lines one pixel width. This assumption is natural for a range sensor to acquire range data in a 3D real world environment. Both edge information of the intensity image and linear interpolation of the range data are used. Experiments show that this method gives very good results in inferring missing range data. It outperforms both the previous method and bilinear interpolation when a very small percentage of range data is known.