Real-time visual tracking of a moving object using pan and tilt platform: A Kalman filter approach

This paper presents a vision-based navigation strategy for a pan and tilt platform and a mounted video camera as a visual sensor. For detection of objects, a suitable image processing algorithm is used. Moreover, estimation of the object position is performed using the Kalman filter as an estimator. The proposed method is implemented experimentally to a laboratory-size pan and tilt platform. Experimental results show good target tracking by the proposed method in real-time.

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