A NEURAL ALGORITHM FOR ESTIMATING THE 3D RIGID BODIES''''MOTION PARAMETERS
一种三维刚体运动参数鲁棒估计的神经算法

This paper deals with estimating the rigid bodies' motion parameters from token correspondence between two perspective views. Total least square(TLS) method is used to solve the linear equations of motion estimation. Then a minor component analysis (MCA) neuron is constructed to get the TLS solution. Finally a outline resisting version of the learning rule is developed by using the statistical approach. Comparative experiments have been made and results show that our robust rules improve the performance significantly when outliers are presented.