RANSAC算法

Question

任何人都可以告诉我如何使用RANSAC算法来选择两个图像中具有特定重叠部分的共同特征点？问题是从基于特征的图像拼接中产生的。

Answer 1

我实现了一个图像拼接几年回来。维基百科上的RANSAC文章很好地描述了一般的algortihm。

当使用RANSAC进行基于特征的图像匹配时，您想要找到将第一幅图像转换为第二幅图像的变换。这将是维基百科文章中描述的模型。

如果您已经获得了两张图片的特征，并且发现第一张图片中的哪些特征与第二张图片中的哪些特征最匹配，则可以使用RANSAC。

The input to the algorithm is: 
n - the number of random points to pick every iteration in order to create the transform. I chose n = 3 in my implementation. 
k - the number of iterations to run 
t - the threshold for the square distance for a point to be considered as a match 
d - the number of points that need to be matched for the transform to be valid 
image1_points and image2_points - two arrays of the same size with points. Assumes that image1_points[x] is best mapped to image2_points[x] accodring to the computed features. 

best_model = null 
best_error = Inf 
for i = 0:k 
    rand_indices = n random integers from 0:num_points 
    base_points = image1_points[rand_indices] 
    input_points = image2_points[rand_indices] 
    maybe_model = find best transform from input_points -> base_points 

    consensus_set = 0 
    total_error = 0 
    for i = 0:num_points 
    error = square distance of the difference between image2_points[i] transformed by maybe_model and image1_points[i] 
    if error < t 
     consensus_set += 1 
     total_error += error 

    if consensus_set > d && total_error < best_error 
    best_model = maybe_model 
    best_error = total_error 

最终结果是将image2中的点最佳转换为image1的转换，这在拼接时非常实用。