{"title":"Seamless Registration of Multiple Range Images with Whole Block Adjustment","authors":"R. Zhai, Jianqing Zhang, Shunyi Zheng","doi":"10.1109/IMSCCS.2006.122","DOIUrl":null,"url":null,"abstract":"Multiple range images registration is one of the most important problems in range image analysis. This paper proposes a new method to implement seamless registration of multiple range images under least squares, since all the range images constitute a circled network, which can be seen as the closed condition of the whole block adjustment. We experimented on real range images taken by laser scanners, and observed that our method worked successfully even for noise data, and it reduces significantly the level of the registration errors between all pairs in a set of range images. The proposed method has the distinct advantage of seamless and robustness","PeriodicalId":202629,"journal":{"name":"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"First International Multi-Symposiums on Computer and Computational Sciences (IMSCCS'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMSCCS.2006.122","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Multiple range images registration is one of the most important problems in range image analysis. This paper proposes a new method to implement seamless registration of multiple range images under least squares, since all the range images constitute a circled network, which can be seen as the closed condition of the whole block adjustment. We experimented on real range images taken by laser scanners, and observed that our method worked successfully even for noise data, and it reduces significantly the level of the registration errors between all pairs in a set of range images. The proposed method has the distinct advantage of seamless and robustness