Making good features track better
Tommasini, T.
Fusiello, A.
Trucco, E.
Roberto, V.
Machine Vision Lab., Udine Univ.;
This paper appears in: Computer Vision and Pattern Recognition, 1998. Proceedings. 1998 IEEE Computer Society Conference on
Publication Date: 23-25 Jun 1998
On page(s): 178-183
Meeting Date: 06/23/1998 - 06/25/1998
Location: Santa Barbara, CA, USA
ISSN: 1063-6919
ISBN: 0-8186-8497-6
References Cited: 17
INSPEC Accession Number: 5985842
Digital Object Identifier: 10.1109/CVPR.1998.698606
Current Version Published: 2002-08-06
Abstract
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
Index
Terms
Available to subscribers and IEEE members.
References
Available to subscribers and IEEE members.
Citing Documents
Available to subscribers and IEEE members.
Cart
