Neural networks for 3D rigid motion estimation
Yimin Xia · Jisuanji gongcheng yu sheji · 2008
Neural networks is used to estimate three-dimensional(3D) rigid motion parameters based two constraints.The one is based on 3D correspondences.The points' coordinates before motion are updated by the presupposed motion parameters and then compared to those after motion.The other is based two-dimensional(2D) motion fields.The motion fields from presupposition are compared to those computed from image sequences.Both network updates its weights by newton-raphson procedure for minimizing the error measures.Experimental results are presented for validating the proposed scheme.