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Vision-based target tracking and surveillance with robust set-valued state estimation

journal contribution
posted on 2010-03-01, 00:00 authored by Adrian Bishop, A Savkin, Pubudu PathiranaPubudu Pathirana
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.

History

Journal

IEEE signal processing letters

Volume

17

Issue

3

Pagination

289 - 292

Publisher

IEEE

Location

Piscataway, N.J.

ISSN

1070-9908

eISSN

1558-2361

Language

eng

Publication classification

C1 Refereed article in a scholarly journal

Copyright notice

2010, IEEE