ملخص
The adjustment of a straight line through a cloud of points is analyzed for the case where all coordinates are measured quantities and thus affected by random errors. The so-called Total Least-Squares Solution (TLSS) can then be obtained by solving the resulting non-linear normal equations via a newly developed iterative approximation algorithm or, equivalently, by following the smallest eigenvalue approach. After showing the superior performance of the TLS approach in the 2D-case, the procedure is extended to the 3D case where a plane is sought that best fits an observed point cloud. This procedure is implemented in surface reconstruction from a cloud of LIDAR points.
| العنوان المترجم للمساهمة | Total Least-Squares (TLS) for geodetic straight-line and plane adjustment |
|---|---|
| اللغة الأصلية | الإنجليزيّة |
| الصفحات (من إلى) | 141-168 |
| عدد الصفحات | 28 |
| دورية | Bollettino di Geodesia e Scienze Affini |
| مستوى الصوت | 65 |
| رقم الإصدار | 3 |
| حالة النشر | نُشِر - 2006 |
| منشور خارجيًا | نعم |
بصمة
أدرس بدقة موضوعات البحث “Total Least-Squares (TLS) for geodetic straight-line and plane adjustment'. فهما يشكلان معًا بصمة فريدة.قم بذكر هذا
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