Created
July 23, 2018 13:33
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Homography estimation normalization
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| ### normalization so that the points have zero mean and unit standard deviation - important for numerical reasons | |
| m = np.mean(input_points[:2], axis=1) | |
| maxstd = max(np.std(input_points[:2], axis=1)) + 1e-9 | |
| C1 = np.diag([1/maxstd, 1/maxstd, 1]) | |
| C1[0][2] = -m[0]/maxstd | |
| C1[1][2] = -m[1]/maxstd | |
| input_points = np.dot(C1, input_points) |
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