Modeling 3D Quantization Error For Motion Estimation
Free (open access)
L.X. Zhou & W.K. Gu
Spatial anisotropic uncertainty of feature points must be taken into account to improve the precision in visual navigation. This paper includes two parts, which discuss error modeling and motion estimation respectively. In the first part we model the 3D reconstruction uncertainty in binocular stereo system as normal distribution and compute its propagation in stereo pair. Assume the uncertainty of image feature pixels geing normal distributed on the image plane, the reconstructed 3D error is analytically derived based on some error evaluation schemes. The closed-form solution of the 3D uncertainty is obtained for parallel camera setup. The second part of this paper proposes a novel iterative motion estimation algorithm that involves the anisotropic 3D uncertainty.