This paper presents high speed and high accuracy visual servoing system. The algorithm has three major improvements, which can be implemented in practical applications; Firstly high-accuracy pose estimation by using stereo cameras, secondly real time implementation issues with non-real-time image processing platform and thirdly a consideration for industrial position controller. To resolve the issues, position-based visual servoing (PBVS) is adopted and appearance model based virtual visual servoing (VVS) is applied for pose estimation. VVS approach does not compute the stereo matching but directly compares the OpenGL rendered image and camera image for each camera; estimate the position/orientation using VVS independently for each camera; and provides a theoretically optimal compromise among those estimates. To enhance estimation accuracy, a hybrid method of stereo trigonometry for position estimation and weighted least squares for orientation estimation is proposed to combine the information from the stereo cameras. Operation speed is increased by using graphic processing unit (GPU) acceleration and an on-line trajectory generator which can accommodate the variable cycle of the image processing and the fixed cycle of a common robot controller. Finally, some experimental results illustrate the effectiveness of the proposed framework.