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KLT tracking using intrinsic and extrinsic camera parameters in consideration of uncertainty

: Trummer, M.; Denzler, J.; Munkelt, C.

Ranchordas, A.-K.N. ; Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setúbal:
Third International Conference on Computer Vision Theory and Applications, VISAPP 2008. Proceedings. Vol. 1 : Funchal, Madeira, Portugal, 22 - 25 January 2008
Setúbal: INSTICC Press, 2008
ISBN: 978-989-811121-0
ISBN: 978-989-8111-21-0
International Conference on Computer Vision Theory and Applications (VISAPP) <3, 2008, Funchal>
Fraunhofer IOF ()
feature tracking; epipolar geometry; reconstruction

Feature tracking is an important task in computer vision, especially for 3D reconstruction applications. Such procedures can be run in environments with a controlled sensor, e.g. a robot arm with camera. This yields the camera parameters as special knowledge that should be used during all steps of the application to improve the results. As a first step, KLT (Kanade-Lucas-Tomasi) tracking (and its variants) is an approach widely accepted and used to track image point features. So, it is straightforward to adapt KLT tracking in a way that camera parameters are used to improve the feature tracking results. The contribution of this work is an explicit formulation of the KLT tracking procedure incorporating known camera parameters. Since practical applications do not run without noise, the uncertainty of the camera parameters is regarded the procedure. Comparing practical experiments have been performed and the results are presented.