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From 3d point cloud to disparity map

Using a stereo calibrated rig of cameras, Ive obtained a disparity map. Using the reprojectImageTo3D() function, I have the 3d point cloud. I want to do some filtering and segmentation on the point cloud and after that re-render it to a disparity image.

Is there an elegant way to do this? I know about projectPoints() and I found this rendering example but it offers a free way of viewing the point cloud. I would like to simulate it so the output I get is actually the same as the disparity map.