Wide Baseline Matching using Triplet Vector Descriptor

We propose an image matching method using triplet vector descriptor. The triplet vector descriptor consists of two different types of affine invariants: the gray level profile between two feature points and the two covariance matrices of those points. In order to establish point matches, we first vote the similarities of the triplet vector descriptors into candidate matches, and then, we verify the matches by normalized triangular region vectors, which are also affine invariant. After enforcing the uniqueness of the candidate matches, we finally adopt RANSAC with the epipolar constraint for removing outliers. By using our method, we can obtain correct matches on wide baseline matching problems. We show the effectiveness of our method by real image examples.