A Kalman-Filter-Based Method for Real-Time Visual Tracking of a Moving Object Using Pan and Tilt Platform

Abstract— The problem of real time estimating position and orientation of a moving object is an important issue for vision-based control of pan and tilt. 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.