{"title":"使用骨架进行对象对齐的3D变换的自动估计","authors":"Tao Wang, A. Basu","doi":"10.1109/ICPR.2006.298","DOIUrl":null,"url":null,"abstract":"An algorithm for automatic estimation of 3D transformations between two objects is presented in this paper. Skeletons of the 3D objects are created using a fully parallel thinning technique, feature point pairs (land markers) are automatically extracted from skeletons, and a least squares method is applied to solve an over determined linear system to estimate the 3D transformation matrix. Experiments show that this method is quite accurate when the translations and rotation angles are small, even when there is some noise in the data. The estimation process requires about 2 seconds on an Intel Centrino Laptop with 512 MB memory, for a complex model with about 37,000 object points and 500 object points for its skeletons","PeriodicalId":236033,"journal":{"name":"18th International Conference on Pattern Recognition (ICPR'06)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Automatic Estimation of 3D Transformations using Skeletons for Object Alignment\",\"authors\":\"Tao Wang, A. Basu\",\"doi\":\"10.1109/ICPR.2006.298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm for automatic estimation of 3D transformations between two objects is presented in this paper. Skeletons of the 3D objects are created using a fully parallel thinning technique, feature point pairs (land markers) are automatically extracted from skeletons, and a least squares method is applied to solve an over determined linear system to estimate the 3D transformation matrix. Experiments show that this method is quite accurate when the translations and rotation angles are small, even when there is some noise in the data. The estimation process requires about 2 seconds on an Intel Centrino Laptop with 512 MB memory, for a complex model with about 37,000 object points and 500 object points for its skeletons\",\"PeriodicalId\":236033,\"journal\":{\"name\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"volume\":\"63 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th International Conference on Pattern Recognition (ICPR'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICPR.2006.298\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th International Conference on Pattern Recognition (ICPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2006.298","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Estimation of 3D Transformations using Skeletons for Object Alignment
An algorithm for automatic estimation of 3D transformations between two objects is presented in this paper. Skeletons of the 3D objects are created using a fully parallel thinning technique, feature point pairs (land markers) are automatically extracted from skeletons, and a least squares method is applied to solve an over determined linear system to estimate the 3D transformation matrix. Experiments show that this method is quite accurate when the translations and rotation angles are small, even when there is some noise in the data. The estimation process requires about 2 seconds on an Intel Centrino Laptop with 512 MB memory, for a complex model with about 37,000 object points and 500 object points for its skeletons