东南大学学报（英文版）2003，Vol.19Issue(1)：58-63,6.
基于CMAC神经网络和Kalman滤波器的三维视觉跟踪
3-D visual tracking based on CMAC neural network and Kalman filter
摘要
Abstract
In this paper, the Kalman filter is used to predict image feature position aroun dwhich an image-processing window is then established to diminish feature-sea rching area and to heighten the image-processing speed. According to the fundam entals of image-based visual servoing (IBVS), the cerebellar model articulation controller (CMAC) neural network is inserted into the visual servo control loop to implement the nonlinear mapping from the error signal in the image space to the control signal in the input space instead of the iterative adjustment and co mplicated inverse solution of the image Jacobian. Simulation results show that the feature point can be predicted efficiently using the Kalman filter and on-line supervised learning can be realized using CMAC neural network; end-effector can track the target object very well.关键词
视觉跟踪/CMAC/神经网络/Kalman滤波器Key words
visual tracking/CMAC/neural network/Kalman filter分类
信息技术与安全科学引用本文复制引用
王化明,罗翔,朱剑英..基于CMAC神经网络和Kalman滤波器的三维视觉跟踪[J].东南大学学报（英文版）,2003,19(1):58-63,6.基金项目
The National Natural Science Foundation of China (5 9990470). （5 9990470）
