Chang W.-YCHU-SONG CHEN2023-06-092023-06-09200410514651https://www.scopus.com/inward/record.uri?eid=2-s2.0-10044280131&doi=10.1109%2fICPR.2004.1334517&partnerID=40&md5=83146622b319ecff728ab05752773de3https://scholars.lib.ntu.edu.tw/handle/123456789/632543Pose estimation of a multiple camera system (MCS) is usually achieved by either solving the PnP problem or finding the least-squared-error rigid transformation between two 3D point sets. These methods employ partial information of an MCS, in which only a small number of features in one or two cameras can be utilized. To overcome this limitation, we propose a new pose estimation method for an MCS that uses complete information of an MCS. In our method, we treat the MCS as a single generalized camera [7][14] and formulate this problem in a least-squared manner. An iterative algorithm is proposed for solving the least-squared problem. From the experimental results, it shows that the proposed method is accurate for pose estimation of MCS.Least-square-error (LSE); Least-squared problem; Multiple camera system (MCS); Rigid transformations; Algorithms; Image analysis; Iterative methods; Mathematical models; Parameter estimation; Photographic films; Problem solving; Camerasconference paper10.1109/ICPR.2004.13345172-s2.0-10044280131