PERFORMANCE EVALUATION OF FEATURE DETECTION FOR LOCAL OPTICAL FLOW TRACKING

Tobias Senst, Brigitte Unger, Ivo Keller, Thomas Sikora

2012

Abstract

Due to its high computational efficiency the Kanade Lucas Tomasi feature tracker is still widely accepted and a utilized method to compute sparse motion fields or trajectories in video sequences. This method is made up of a Good Feature To Track feature detection and a pyramidal Lucas Kanade feature tracking algorithm. It is well known that the Good Feature To Track takes into account the Aperture Problem, but it does not consider the Generalized Aperture Problem. In this paper we want to provide an evaluation of a set of alternative feature detection methods. These methods are taken from feature matching techniques like FAST, SIFT and MSER. The evaluation is based on the Middlebury dataset and performed by using an improved pyramidal Lucas Kanade method, called RLOF feature tracker. To compare the results of the feature detector and RLOF pair, we propose a methodology based on accuracy, efficiency and covering measurements.

Paper Citation

in Harvard Style

Senst T., Unger B., Keller I. and Sikora T. (2012). PERFORMANCE EVALUATION OF FEATURE DETECTION FOR LOCAL OPTICAL FLOW TRACKING . In Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM, ISBN 978-989-8425-99-7, pages 303-309. DOI: 10.5220/0003731103030309

in Bibtex Style

@conference{icpram12,
author={Tobias Senst and Brigitte Unger and Ivo Keller and Thomas Sikora},
title={PERFORMANCE EVALUATION OF FEATURE DETECTION FOR LOCAL OPTICAL FLOW TRACKING},
booktitle={Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,},
year={2012},
pages={303-309},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003731103030309},
isbn={978-989-8425-99-7},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods - Volume 2: ICPRAM,
TI - PERFORMANCE EVALUATION OF FEATURE DETECTION FOR LOCAL OPTICAL FLOW TRACKING
SN - 978-989-8425-99-7
AU - Senst T.
AU - Unger B.
AU - Keller I.
AU - Sikora T.
PY - 2012
SP - 303
EP - 309
DO - 10.5220/0003731103030309