More details to come, but I was comparing the performance of OpenCV to Matlab Computer Vision Toolbox for the dense estimates of optical flow given by the Horn Schunck algorithm. I was getting a very different result with OpenCV vs. Matlab for the Optical Flow Estimation. It seemed that OpenCV was washing out fine details in the optical flow. After carefully comparing Matlab Computer Vision and OpenCV outputs for Horn Schunck optical flow, I found that the default lambda/smoothness parameter of 1.0 for `cv.``CalcOpticalFlowHS` is not the same as what Matlab calls 1.0.

I need to quantify this further, but for now I found that in OpenCV `cv.``CalcOpticalFlowHS` setting lambda=0.001 gives results that are much more like Matlab–I can see the fine details. This is just a rough guess, if I have time I’ll quantify it in my forthcoming article on segmenting terabtyes of aurora borealis video in an hour!