Background model technique with disparity map
If I have generated a disparity map or depth map using StereoBM then what is the best way to look for change detection in the scene? I've tried using MOG2 and other background models but in general there are just too many fluctuations (speckle noise) in the disparity map to make this viable. Is there a better way in opencv to look for change detection from stereo data?
Assuming the stereo camera is not moving, why not use the rgb or greyscale images with MOG2 to give you a mask to apply to the 3D data?
In general I find the RGB or greyscale isn't robust enough for my purposes and is one reason why I moved to a stereo camera. The 3-D geometry makes it possible to threshold out certain planes not of interest to me. I had hoped that there would then be some standard way to use a background model with 3-D data.
The OpenCV stereo algorithms are not all that great. They are very fast, but they lack accuracy and detail. If accurate and stable depth is what you want, stop wasting your time and move to a structured light depth camera like the Kinect or the Intel offerings.