期刊全称 | Advanced Procrustes Analysis Models in Photogrammetric Computer Vision | 影响因子2023 | Fabio Crosilla,Alberto Beinat,Domenico Visintini | 视频video | | 发行地址 | Unique reference for Procrustean methods applied to Photogrammetry and Computer Vision.Innovative and unconventional mathematical approach to fundamentals of Photogrammetry and Computer Vision.Complem | 学科分类 | CISM International Centre for Mechanical Sciences | 图书封面 |  | 影响因子 | .This book gives a comprehensive view of the developed procrustes models, including the isotropic, the generalized and the anisotropic variants. These represent original tools to perform, among others, the bundle block adjustment and the global registration of multiple 3D LiDAR point clouds. Moreover, the book also reports the recently derived total least squares solution of the anisotropic Procrustes model, together with its practical application in solving the exterior orientation of one image. The book is aimed at all those interested in discovering valuable innovative algorithms for solving various photogrammetric computer vision problems. In this context, where functional models are non-linear, Procrustean methods prove to be powerful since they do not require any linearization nor approximated values of the unknown parameters, furnishing at the same time results comparable in terms of accuracy with those given by the state-of-the-art methods.. | Pindex | Book 2019 |
The information of publication is updating
|
|