This paper describes research of using area of artificial mark on vision based head tracker system. A head tracker system consists of the translational and rotational motions which are detected by web camera. Results of the motion are taken from image processing and neural network. Because of the characteristics of cockpit, the specific color on the helmet is tracked for translational motion. And rotational motion is tracked via neural network. Ratio of two different colored area on the helmet is used as input of network. Neural network algorithms used, such as back-propagation and RBFN (Radial Basis Function Network). Both back-propagation using a characteristic of feedback and RBFN using a characteristic of statistics have a good performances for the tracking of nonlinear system such as a head motion. Finally, this paper analyzes and compares with tracking performance.