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Managing redundant visual measurements for accurate pose tracking

Published online by Cambridge University Press:  02 March 2021

Vincenzo Lippiello  and
Luigi Villani
Vincenzo Lippiello*
Affiliation:
PRISMA Lab., Dipartimento di Informatica e Sistemistica, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy)
Luigi Villani*
Affiliation:
PRISMA Lab., Dipartimento di Informatica e Sistemistica, Università degli Studi di Napoli Federico II, Via Claudio 21, 80125 Napoli (Italy)
*
Email: vincenzo.lippiello@unina.it
Email: luigi.villiani@unina.it
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Summary

This paper proposes an algorithm for managing redundant measurements provided by a stereo multi-camera system to achieve accurate visual tracking of a moving object. Selfocclusion, different visual resolution zones and optimal selection of redundant measurements are some of the problems addressed. The algorithm uses the extended Kalman filter embedded in a computational efficient pose estimation procedure based on Binary Space Partitioning Tree geometric modelling of 3D objects. Experimental results are presented for the case of an object moving in the visual space of two fixed cameras.

Keywords

Pose trackingVisual dataRedundant measurementsKalman filter

Information

Type
Research Article
Information
Robotica , Volume 21 , Issue 5 , October 2003 , pp. 511 - 519
Copyright
Copyright © Cambridge University Press 2003

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