Feature Point Matching Based on Affine Iterative Model
基于仿射迭代模型的特征点匹配算法

Feature point matching is a key problem of computer vision and is frequently used in object recognition,image retrieval and 3D reconstruction and so on.In this paper,an accurate feature points matching method for two-frame images was proposed.Since it was proved that the homography between two windows of corresponding feature can be geometrically approximated by an affine transformation model.The projective distortion of windows of corresponding feature was estimated and rectified by a fast iterative scheme based on the affine transformation model.At the same time,the location error of corresponding feature points produced at the feature detection stage was compensated using the estimated affine parameters.The matching results of corresponding feature points can achieve sub-pixel precision,which effectively improve the precisions of the final epipolar geometry.Experimental results of real images and the comparisons with other methods strongly demonstrate the validity and accuracy of the algorithm.