Tracking in a Hough Space with the Extended Kalman Filter
Steven J. Mills, Tony Pridmore, Matthew Hills · 2003
A combined tracking method using the Kalman filter and Hough transform is presented. An extended Kalman filter is used to model the parameters and motion of a set of lines detected in a Hough space The integration of these two techniques gives a number of advantages. The use of a Hough transform provides resilience to noise and partial occlusion, and the Kalman filter’s ability to predict future states is used to reduce the computational load of line detection. Analysis of the tracker from synthetic data shows that it is robust to noise, occlusion, and deviations from the constant motion model underlying the Kalman filter. Tracking results from video sequences illustrate its applicability to real-world domains. 1