A depth sensor or depth camera is available at a reasonable cost in recent years. Due to the excessive dispersion of depth values outputted from the depth camera, however, changes in the pose cannot be directly employed for complicated hand pose estimation. The authors therefore propose a visual-servoing controlled robotic hand with RGB high-speed cameras. Two cameras have their own database in the system. Each data set has proportional information of each hand image and image features for matching, and joint angle data for output as estimated results. Once sequential hand images are recorded with two high-speed RGB cameras, the system first selects one database with bigger size of hand region in each recorded image. Second, a coarse screening is carried out according to the proportional information on the hand image which roughly corresponds to wrist rotation, or thumb or finger extension. Third, a detailed search is performed for similarity among the selected candidates. The estimated results are transmitted to a robot hand so that the same motions of an operator is reconstructed in the robot without time delay.