Yes, simple window correlation on the epipolar line, but with some personal refinements I can't remember for now. I remember testing Pearson product-moment correlation coefficient to rule out outliers which gave better results in some cases though.FingerFlinger wrote:By the way, I assume that your code does straight-forward patch correlation? What window size are you using?
For the window I've tried several sizes, 3x3 was somewhat acceptable and 7x3 was a good compromise in speed vs quality IIRC, on quite low resolution images. My machine at the time was not beefy enough to work on HD images (older AMD Athlon single processor).
Ah yes, I guess it's related to the census algorithm then. I thought it was pretty good since the 2nd best algorithm is using it in the Middlebury evaluation, but it's in fact AD-census, census coupled with absolute differences measure.FingerFlinger wrote:EDIT: This one is from "FPGA Design and Implementation of a Real-Time Stereo Vision System", and is also based on the Census transform. You can see that their results are almost identical to mine.