Robust Pan, Tilt and Zoom Estimation for PTZ Camera by Using Meta Data and/or Frame-to-Frame Correspondences

Author

Wu, Shunguang ; Zhao, Tao ; Broaddus, Christopher ; Yang, Changjiang ; Aggarwal, Manoj

Author_Institution

Sarnoff Corp., Princeton, NJ

fYear

2006

fDate

5-8 Dec. 2006

Firstpage

1

Lastpage

7

Abstract

An algorithm to estimate pan, tilt and zoom (PTZ) parameters of a PTZ camera from meta data and frame-to-frame (F2F) correspondences at different sampling rates is proposed in a real-time video surveillance and automatic object tracking system. Two extended Kalman filters are designed to simultaneously estimate zoom and pan-tilt parameters. Uncorrelated constant velocity models are used to model the kinematics of focal length, pan and tilt motions, while the F2F homography is employed to model the relative motion of the camera. Experiment results from both synthetic and realtime system data demonstrate that the F2F correspondence information can enhance the PTZ estimation accuracy as long as its error is smaller than a particular threshold

Keywords

Kalman filters; computer vision; meta data; motion control; motion estimation; pose estimation; robust control; surveillance; target tracking; video cameras; video signal processing; automatic object tracking system; camera motion; extended Kalman filter; frame-to-frame correspondence; frame-to-frame homography; metadata; pan-tilt-zoom camera; real-time video surveillance; robust control; Cameras; Frequency estimation; Image sequences; Kinematics; Motion estimation; Parameter estimation; Real time systems; Robustness; Sampling methods; Video surveillance;

fLanguage

English

Publisher

ieee

Conference_Titel

Control, Automation, Robotics and Vision, 2006. ICARCV '06. 9th International Conference on

Conference_Location

Singapore

Print_ISBN

1-4244-0341-3

Electronic_ISBN

1-4214-042-1

Type

conf

DOI

10.1109/ICARCV.2006.345423

Filename

4150227