Least-Squares Fitting of Two 3-D Point Sets

  • Authors:
  • K. S. Arun;T. S. Huang;S. D. Blostein

  • Affiliations:
  • -;-;-

  • Venue:
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Year:
  • 1987

Quantified Score

Hi-index 0.15

Visualization

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