Least-squares fitting of two 3-d point sets

Two point sets {pi} and {p'i}; i = 1, 2,..., N are related by p'i = Rpi + T + Ni, where R is a rotation matrix, T a translation vector, and Ni a noise vector. Given {pi} and {p'i}, we present an algorithm for finding the least-squares solution of R and T, which is based on the singula...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 9(1987), 5 vom: 01. Mai, Seite 698-700
1. Verfasser: Arun, K S (VerfasserIn)
Weitere Verfasser: Huang, T S, Blostein, S D
Format: Aufsatz
Sprache:English
Veröffentlicht: 1987
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Journal Article
Beschreibung
Zusammenfassung:Two point sets {pi} and {p'i}; i = 1, 2,..., N are related by p'i = Rpi + T + Ni, where R is a rotation matrix, T a translation vector, and Ni a noise vector. Given {pi} and {p'i}, we present an algorithm for finding the least-squares solution of R and T, which is based on the singular value decomposition (SVD) of a 3 × 3 matrix. This new algorithm is compared to two earlier algorithms with respect to computer time requirements
Beschreibung:Date Completed 02.10.2012
Date Revised 12.11.2019
published: Print
Citation Status PubMed-not-MEDLINE
ISSN:1939-3539