Comparison of Optical Flow Methods under Stereomatching with Short Baselines

Abstract

This article studies the effectiveness of optical flow methods applied to short baseline image pairs under different noise levels. New metrics have been developed to analyze the results because the usual metrics are inadequate in a subpixel context. We have used the implementation of some standard optical flow methods adapted to the stereo problem. Our experiments show that the Brox et al. method produces the least errors, with a 60% success rate and a relative precision at 1/100th of a pixel. On the other hand, our comparison shows that a discontinuity preserving method, derived from Brox et al., also provides competitive results at the same time that it yields disparities with more details and correct contours. Source Code Source codes of Lucas-Kanade 1D, Robust Optical Flow 1D and Robust Discontinuity Preserving 1D algorithms are provided in the web page of the article 1 .

Cloud Detection by Luminance and Inter-band Parallax Analysis for Pushbroom Satellite Imagers

“…It is preferred here because it has an automatic mechanism to weight the flow regularization term and preserve discontinuities. As shown in [2] its results are accurate. The functional to minimize is defined by Table summarizing the parameters of the proposed method.…”