Fast and close-form optimal estimation of absolute orientation problem

A fast algorithm to solve the absolate orientation problem is proposed. The algorithm first formulates objective function by least square method. Then it decouples the rotation and translation. Finally it uses the Fobenius norm, determinant and adjoint matrix to formulate the close-form optimal estimation of the rotation and translation. The proposed algorithm has high accuracy and noise-resistance, especially high computation speed because of the absence of singular value decomposition, which is commonly used in current employed algorithms. Results of numerical experiment show that, compared with Umeyama algorithm, one of the best absolute orientation algorithms, the proposed algorithm performs the same level of accuracy and noise-resistance and extremely faster speed, and it is suitable for the areas which require high real-time performance.