Stereo-vision-based moving object tracking via robust linear filtering
Pathirana, Pubudu, Bishop, Adrian and Savkin, Andrey 2007, Stereo-vision-based moving object tracking via robust linear filtering, in Proceedings of the 2007 Intelligent Sensors, Sensor Networks & Information Processing Conference, Institute of Electrical and Electronics Engineers (IEEE), Piscataway, N.J., pp. 221-226.
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Title
Stereo-vision-based moving object tracking via robust linear filtering
International Conference on Intelligent Sensors, Sensor Networks and Information
Start page
221
End page
226
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Place of publication
Piscataway, N.J.
Summary
Vision-based tracking sensors typically provide nonlinear measurements of the targets Cartesian position and velocity state components. In this paper we derive linear measurements using an analytical measurement conversion technique which can be used with two (or more) vision sensors. We derive linear measurements in the target’s Cartesian position and velocity components and we derive a robust version of a linear Kalman filter. We show that our linear robust filter significantly outperforms the extended Kalman Filter. Moreover, we prove that the state estimation error is bounded.
ISBN
1424415020 9781424415021
Language
eng
Field of Research
010203 Calculus of Variations, Systems Theory and Control Theory
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