A robust visual tracking of an arbitrary-shaped object by a new active contour method for a virtual reality application

This paper presents a real-time, highly reliable, open field visual tracking system, which can automatically detect an arbitrary-shaped object in 3-D space and find out its location so that the 2-DOF camera platform can be controlled to keep the target centered in the monitor image. The total processing period of the proposed visual servo system is less than 34 ms. Next, the visual servo system is to play the role as a military light-of-sight on the air fighter to lock an enemy fighter. Incidentally, the 2-DOF information of the camera platform is adopted to the autopilot control of an air fighter to track the foregoing target. The overall system is experimented and verified in a virtual reality environment, which can further be developed as an entertainment or military training platform.

[1]  Roberto Brunelli,et al.  MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES , 2001 .

[2]  Joachim Denzler,et al.  A two stage real-time object tracking system , 1994 .

[3]  Jerry L. Prince,et al.  Snakes, shapes, and gradient vector flow , 1998, IEEE Trans. Image Process..

[4]  Eric Nettleton,et al.  Real time Multi-UAV Simulator , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[5]  Demetri Terzopoulos,et al.  Snakes: Active contour models , 2004, International Journal of Computer Vision.

[6]  Nicu Sebe,et al.  Improving visual matching , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[7]  Yi-Ping Hung,et al.  Fast block matching algorithm based on the winner-update strategy , 2001, IEEE Trans. Image Process..

[8]  Y. Bar-Shalom,et al.  Tracking in a cluttered environment with probabilistic data association , 1975, Autom..

[9]  H. Niemann,et al.  A New Energy Term Combining Kalman{Filter and Active Contour Models for Object Tracking , 1996 .

[10]  Yi-Ping Hung,et al.  A Fast Block Matching Algorithm Based on the Winner-Update Rule , 2000 .

[11]  Stanley T. Birchfield,et al.  Elliptical head tracking using intensity gradients and color histograms , 1998, Proceedings. 1998 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (Cat. No.98CB36231).

[12]  Mubarak Shah,et al.  A Fast algorithm for active contours and curvature estimation , 1992, CVGIP Image Underst..

[13]  Michael Isard,et al.  CONDENSATION—Conditional Density Propagation for Visual Tracking , 1998, International Journal of Computer Vision.

[14]  S. Birchfield,et al.  An elliptical head tracker , 1997, Conference Record of the Thirty-First Asilomar Conference on Signals, Systems and Computers (Cat. No.97CB36136).