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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 Ã 3 matrix. This new algorithm is compared to two earlier algorithms with respect to computer time requirements.
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