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CVPR
1998
IEEE

Making Good Features Track Better

9 years 11 months ago
Making Good Features Track Better
This paper addresses robust feature tracking. We extend the well-known Shi-Tomasi-Kanade tracker by introducing an automatic scheme for rejecting spurious features. We employ a simple and efficient outlier rejection rule, called X84, and prove that its theoretical assumptions are satisfied in the feature tracking scenario. Experiments with real and synthetic images confirm that our algorithm makes good features track better; we show a quantitative example of the benefits introduced by the algorithm for the case of fundamental matrix estimation. The complete code of the robust tracker is available via ftp.
Tiziano Tommasini, Andrea Fusiello, Emanuele Trucc
Added 12 Oct 2009
Updated 30 Oct 2009
Type Conference
Year 1998
Where CVPR
Authors Tiziano Tommasini, Andrea Fusiello, Emanuele Trucco, Vito Roberto
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