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Issue No.05 - May (1987 vol.9)
pp: 698-700
K. S. Arun , Coordinated Science Laboratory, University of Illinois, Urbana, IL 61801.
T. S. Huang , Coordinated Science Laboratory, University of Illinois, Urbana, IL 61801.
S. D. Blostein , Coordinated Science Laboratory, University of Illinois, Urbana, IL 61801.
ABSTRACT
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.
CITATION
K. S. Arun, T. S. Huang, S. D. Blostein, "Least-Squares Fitting of Two 3-D Point Sets", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol.9, no. 5, pp. 698-700, May 1987, doi:10.1109/TPAMI.1987.4767965
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