Model-based object recognition using camera control

We propose a robust object recognition system based on the control of viewpoint. 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 action plan iteratively so as to decrease the degree of recognition-ambiguity and controls the camera to move to the optimum position. Therefore, our proposed method is able to recognize the object more accurately than conventional methods which use a given input image. Experimental results show the effectiveness of our approach.