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Viewpoint calibration is a method to manipulate hand-eye for generating calibration parameters for active viewpoint control and object grasping. This paper presents a new approach to hand-eye robotic calibration for vision-based object modeling and grasping. Our method provides a 1.0 pixel level of image registration accuracy when a standard Puma robot generates an arbitrary viewpoint. In order to attain this accuracy, our new formalism of hand-eye calibration deals with a lens distortion model of a vision sensor and utilizes a new parameter estimation algorithm using an extended Kalman filter. We demonstrate the power of this new method called "SmartView" for: 1) generating 3D object models using an interactive 3D modeling editor; 2) recognizing 3D objects using stereo vision systems; and 3) grasping 3D objects using a manipulator. Experimental results using a Puma robot are shown.