This paper proposes a robust object recognition system based on camera control. The objective of our system is to seek the optimum camera position where the unknown object can be recognized clearly. We define a degree of recognition-ambiguity based on basic probabilities that is calculated by using an input image and model images generated from object model data. Our active vision system makes an act plan iteratively so as to decrease the degree of recognition-ambiguity and controls the camera to move to the optimum position. Our proposed active method is able to recognize the object more accurately than conventional passive methods which analyze only a given input image. Experimental results show effectiveness of our approach.