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Abstract:
The presented work is motivated by the problem of local motion estimation via robust regression with linear models. In order to increase the robustness of the motion estimates we propose a novel Robust Local Optical Flow approach based on a modified Hampel estimator. We show the deficiencies of the least squares estimator used by the standard KLT tracker when the assumptions made by Lucas/Kanade are violated. We propose a strategy to adapt the window sizes to cope with the Generalized Aperture Problem...
Related Publications
2016
- Tobias Senst, Jonas Geistert, Thomas Sikora
Robust local optical flow: Long-range motions and varying illuminations
IEEE International Conference on Image Processing, Phoenix, AZ, USA, 25.09.2016 - 28.09.2016, pp. 4478-4482
IEEE Catalog Number: CFP16CIP-USB ISBN: 978-1-4673-9960-9 DOI:10.1109/ICIP.2016.7533207
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2014
- Tobias Senst, Thilo Borgmann, Ivo Keller, Thomas Sikora
Cross based Robust Local Optical Flow
21th IEEE International Conference on Image Processing, Paris,France, 27.10.2014 - 30.10.2014, pp. 1967-1971
ISBN: 978-1-4799-5750-7 DOI:10.1109/ICIP.2014.7025394
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2013
- Tobias Senst, Jonas Geistert, Ivo Keller, Thomas Sikora
Robust Local Optical Flow Estimation using Bilinear Equations for Sparse Motion Estimation
20th IEEE International Conference on Image Processing, Melbourne, Australia, 15.09.2013 - 18.09.2013, pp. 2499--2503
DOI:10.1109/ICIP.2013.6738515
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2012
- Tobias Senst, Volker Eiselein, Thomas Sikora
Robust Local Optical Flow for Feature Tracking
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), IEEE, vol. 22, no. 9, September 2012, pp. 1377--1387
ISSN={1051-8215}, DOI=10.1109/TCSVT.2012.2202070
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2011
- Tobias Senst, Volker Eiselein, Rubén Heras Evangelio, Thomas Sikora
Robust Modified L2 Local Optical Flow Estimation and Feature Tracking
IEEE Workshop on Motion and Video Computing (WMVC), Kona, USA, 05.01.2011 - 07.01.2011, pp. 685--690
IEEE Catalog Number: CFP11082-CDR ISBN: 978-1-4244-9495-8 DOI: 10.1109/WACV.2011.5711571
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