期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2002
卷号：XXXIV Part 3 A
页码：15-22
出版社：Copernicus Publications
摘要：Factorization algorithms for recovering structure and motion from an image stream have many advantages, but tradition- ally requires a set of well tracked feature points. This limits the usability since, correctly tracked feature points are not available in general. There is thus a need to make factorization algorithms deal successfully with incorrectly tracked feature points. We propose a new computationally efficient algorithm for applying an arbitrary error function in the factorization scheme, and thereby enable the use of robust statistical techniques and arbitrary noise models for individual feature points. These techniques and models effectively deal with feature point noise as well as feature mismatch and missing features. Fur- thermore, the algorithm includes a new method for Euclidean reconstruction that experimentally shows a significant improvement in convergence of the factorization algorithms. The proposed algorithm has been implemented in the Christy–Horaud factorization scheme and the results clearly illus- trate a considerable increase in error tolerance
关键词：Robust statistics; feature tracking; Euclidean reconstruction; structure from motion
