A factorization algorithm for trifocal tensor estimation

Abstract

Trifocal tensor encapsulates the geometric constraints between three views. It plays an important role in computer vision. However elements in measurement matrix of existing linear trifocal tensor estimation algorithms are products of several measurement data, which can amplify measurement error. The factorization algorithm of trifocal tensor estimation is presented, which can overcome this shortcoming. To overcome the deficiency that the extended solution space of factorization algorithm may result in an unstable solution, some modifications are adopted. Synthetic and real image data experiments show that the proposed algorithm is accurate and robust. This provides a new way different from normalized linear algorithm to improve performance of linear algorithm.