Title :
Entropy based camera control for visual object tracking
Author :
Zobel, Matthias ; Denzler, Joachim ; Niemann, Heinrich
Author_Institution :
Erlangen-Nurnberg Univ., Erlangen, Germany
Abstract :
In active visual 3D object tracking, one goal is to control the pan and tilt axes of the involved cameras to keep the tracked object in the centers of the fields of view. We present a novel method, based on an information theoretic measure, that manages this task. The main advantage of the proposed approach is that there is no need for an explicit formulation of a camera controller, such as a PID-controller or something similar. For the case of Kalman filter based tracking, we demonstrate the practicability and evaluate the accuracy of the proposed method in simulations as well as in real-time tracking experiments.
Keywords :
Kalman filters; attitude control; entropy; object detection; optical tracking; state estimation; video signal processing; 3D object tracking; Kalman filter; camera control; camera pan axis; camera tilt axis; entropy; information theory; state estimation; visual object tracking; Acceleration; Cameras; Control systems; Control theory; Entropy; Recursive estimation; State estimation; State-space methods; Uncertainty; Velocity control;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1039118