3D translational motion estimation from 2D displacements
Recovering 3D motion parameters from 2D displacements is a difficult task, given the influence of noise contained in these data, which correspond at best to a crude approximation of the real motion field. The need for stability of the system of equations to be solved is therefore essential. We present a novel method based on an unbiased estimator that aims at enhancing this stability and strongly reduces the influence of noise contamination. Experimental results using synthetic and real optical flows are presented to demonstrate the effectiveness of our method in comparison to a set of selected methods.