CROSS BASED ROBUST LOCAL OPTICAL FLOW

In 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 [1] 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.