title: Least-squares fitting of two 3-d point sets.
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.
authors.affiliation: Coordinated Science Laboratory, University of Illinois, Urbana, IL 61801.
authors.forename: K S
authors.initials: KS
authors.lastname: Arun
authors.forename: T S
authors.initials: TS
authors.lastname: Huang
authors.forename: S D
authors.initials: SD
authors.lastname: Blostein