{"title":"Intermediate coordinate based pose non-perspective estimation from line correspondences","authors":"Yujia Cao, Zhichao Cui, Yuehu Liu, Xiaojun Lv, K.C.C. Peng","doi":"10.1145/3444685.3446299","DOIUrl":null,"url":null,"abstract":"In this paper, a non-iterative solution to the non-perspective pose estimation from line correspondences was proposed. Specifically, the proposed method uses an intermediate camera frame and an intermediate world frame, which simplifies the expression of rotation matrix by reducing to the two freedoms from three in the rotation matrix R. Then formulate the pose estimation problem into an optimal problem. Our method solve the parameters of rotation matrix by building the fifteenth-order and fourth-order univariate polynomial. The proposed method can be applied into the pose estimation of the perspective camera. We utilize both the simulated data and real data to conduct the comparative experiments. The experimental results show that the proposed method is comparable or better than existing methods in the aspects of accuracy, stability and efficiency.","PeriodicalId":119278,"journal":{"name":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","volume":"42 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2nd ACM International Conference on Multimedia in Asia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3444685.3446299","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a non-iterative solution to the non-perspective pose estimation from line correspondences was proposed. Specifically, the proposed method uses an intermediate camera frame and an intermediate world frame, which simplifies the expression of rotation matrix by reducing to the two freedoms from three in the rotation matrix R. Then formulate the pose estimation problem into an optimal problem. Our method solve the parameters of rotation matrix by building the fifteenth-order and fourth-order univariate polynomial. The proposed method can be applied into the pose estimation of the perspective camera. We utilize both the simulated data and real data to conduct the comparative experiments. The experimental results show that the proposed method is comparable or better than existing methods in the aspects of accuracy, stability and efficiency.