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Vision-Based Target Tracking and Surveillance With Robust Set-Valued State Estimation
KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP.
2010 (English)In: IEEE Signal Processing Letters, ISSN 1070-9908, E-ISSN 1558-2361, Vol. 17, no 3, 289-292 p.Article in journal (Refereed) Published
Abstract [en]

Tracking a target from a video stream (or a sequence of image frames) involves nonlinear measurements in Cartesian coordinates. However, the target dynamics, modeled in Cartesian coordinates, result in a linear system. We present a robust linear filter based on an analytical nonlinear to linear measurement conversion algorithm. Using ideas from robust control theory, a rigorous theoretical analysis is given which guarantees that the state estimation error for the filter is bounded, i.e., a measure against filter divergence is obtained. In fact, an ellipsoidal set-valued estimate is obtained which is guaranteed to contain the true target location with an arbitrarily high probability. The algorithm is particularly suited to visual surveillance and tracking applications involving targets moving on a plane.

Place, publisher, year, edition, pages
2010. Vol. 17, no 3, 289-292 p.
Keyword [en]
Computer vision, robust estimation, set-valued estimation, target tracking
National Category
Engineering and Technology
URN: urn:nbn:se:kth:diva-27591DOI: 10.1109/LSP.2009.2038772ISI: 000278154200001ScopusID: 2-s2.0-78149231688OAI: diva2:377406
QC 20101214Available from: 2010-12-14 Created: 2010-12-13 Last updated: 2010-12-14Bibliographically approved

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Bishop, Adrian N.
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