HEASK: Robust homography estimation based on appearance similarity and keypoint correspondences
A new loss function is formulated in homography verification. The function combines models of keypoint correspondence fitness and appearance similarity. Keypoint fitness errors are better characterized with a Laplacian distribution. Image similarity is described using the distribution of ECC. The algorithm is realized by an improved RANSAC framework.
homography estimation appearance similarity ransac keypoint consensus