conference paper

Conference/Proceedings21th IEEE International Conference on Image Processing
Start date27.10.2014
End date30.10.2014
Author(s)Tobias Senst, Thilo Borgmann, Ivo Keller, Thomas Sikora
TitleCross based Robust Local Optical Flow
AbstractIn many computer vision applications local optical flow methods are still a widely used. Such methods, like the Pyramidal Lucas Kanade and the Robust Local Optical Flow, have to address the trade--off between run time and accuracy. In this work we propose an extension to these methods that improves the accuracy especially at object boundaries. This extension makes use of the cross based variable support region generation proposed in Zhang2009 accounting for local intensity discontinuities. In the evaluation using Middlebury data set we prove the ability of the proposed extension to increase the accuracy by a slight increase of run time.
Key wordsOptical Flow, KLT, RLOF, Feature Tracking, Cross-based region construction,RLOFLib
NoteISBN: 978-1-4799-5750-7