Search Space Reduction in Optical Tracking

In this paper we present a practical method for reducing the space when searching for point patterns in optically tracked virtual reality applications. The method uses a predictor to estimate the future position of a point. The key idea is to define a metric that determines the quality of the predictor, and use this metric to construct a 3D region around the predicted position of each point. The size and shape of the 3D region is based on the kinematic properties of the predicted point. The 3D region is projected into 2D to obtain the required search window. The contribution of the paper is that the search space can be reduced substantially by making use of adaptive window shapes and sizes.

[1]  Ronald Azuma,et al.  Improving static and dynamic registration in an optical see-through HMD , 1994, SIGGRAPH.

[2]  Clark F. Olson.  Maximum-Likelihood Image Matching , 2002, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Mark A. Livingston,et al.  Superior augmented reality registration by integrating landmark tracking and magnetic tracking , 1996, SIGGRAPH.

[4]  Ronald Azuma,et al.  Recent Advances in Augmented Reality , 2001, IEEE Computer Graphics and Applications.

[5]  Axel Pinz,et al.  A new optical tracking system for virtual and augmented reality applications , 2001, IMTC 2001. Proceedings of the 18th IEEE Instrumentation and Measurement Technology Conference. Rediscovering Measurement in the Age of Informatics (Cat. No.01CH 37188).

[6]  J. C. Mulder,et al.  The personal space station: Bringing interaction within reach , 2002 .

[7]  Robert van Liere,et al.  Optical tracking using projective invariant marker pattern properties , 2003, IEEE Virtual Reality, 2003. Proceedings..

[8]  Klaus Dorfmüller,et al.  Robust tracking for augmented reality using retroreflective markers , 1999, Comput. Graph..

[9]  Axel Pinz,et al.  The integration of optical and magnetic tracking for multi-user augmented reality , 1999, Comput. Graph..