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Proceedings Paper

Predictive visual tracking
Author(s): Albert J. Wavering; Ronald Lumia
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Paper Abstract

Due to delays in image acquisition and processing, prediction is a critical factor for successful visual tracking of moving objects (both for humans and for vision machines). This paper explores some alternative techniques for predicting object motion for the purpose of tracking with an active camera system. In particular, one of our goals is to develop a system that will track an object undergoing `random' motion quite well, but that will track much better (at higher speeds with less lag) if the object settles into a periodic motion of some kind. Rather than identify parameters for specific signal models to accomplish this, we propose to use a finite set of previous joint states for the signal model. The advantages and problems associated with this approach are discussed. Results of experiments using different prediction algorithms with TRICLOPS, a high-performance active vision system, are also presented.

Paper Details

Date Published: 6 August 1993
PDF: 12 pages
Proc. SPIE 2056, Intelligent Robots and Computer Vision XII: Active Vision and 3D Methods, (6 August 1993); doi: 10.1117/12.150188
Show Author Affiliations
Albert J. Wavering, National Institute of Standards and Technology (United States)
Ronald Lumia, National Institute of Standards and Technology (United States)


Published in SPIE Proceedings Vol. 2056:
Intelligent Robots and Computer Vision XII: Active Vision and 3D Methods
David P. Casasent, Editor(s)

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