conference paper


Conference/ProceedingsIEEE International Conference on Image Processing
Start date25.09.2016
End date28.09.2016
AddressPhoenix, AZ, USA
PublisherIEEE
Pages4478-4482
Author(s)Tobias Senst, Jonas Geistert, Thomas Sikora
TitleRobust local optical flow: Long-range motions and varying illuminations
AbstractSparse motion estimation with local optical flow methods is fundamental for a wide range of computer vision application. Classical approaches like the pyramidal Lucas-Kanade method (PLK) or more sophisticated approaches like the Robust Local Optical Flow (RLOF) fail when it comes to environments with illumination changes and/or long-range motions. In this work we focus on these limitations and propose a novel local optical flow framework taking into account an illumination model to deal with varying illumination and a prediction step based on a perspective global motion model to deal with long-range motions. Experimental results shows tremendous improvements, e.g. 56% smaller error for dense motion fields on the KITTI and an about 76% smaller error for sparse motion fields on the Sintel dataset.
Key wordsOptical Flow, RLOF,
NoteIEEE Catalog Number: CFP16CIP-USB
ISBN: 978-1-4673-9960-9
DOI:10.1109/ICIP.2016.7533207
File1496Senst2016.pdf

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