Least-Squares Fitting of Two 3-D Point Sets

作者：K.S. Arun, Thomas S. Huang, Steven D. Blostein · 发表于：IEEE Transactions on Pattern Analysis and Machine Intelligence · 年份：1987 · DOI：10.1109/tpami.1987.4767965 · 被引用次数：3997 · 研究领域：Advanced Vision and Imaging、Robotics and Sensor-Based Localization、Image and Object Detection Techniques

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.