针对重复纹理场景的特征匹配算法

here are lots of outliers when traditional feature matching methods are used to match two images which contain characters, symmetrical objects or other objects contained repetitive texture. The number of outliers is so large in this case that the number of inliers reduces sharply after RANSAC (Random Sample Consensus), which affects the accuracy of camera pose. An inliers retrieval method based on randomized tree is presented. For each point on the current frame, the proposed method creates a set which contains all points on key frame that can match with this point, and utilizes the spatial information of points on key frame to choose the best matching point. Experimental results show that the proposed retrieval method can improve the matching effect when the processed images contain repetitive texture.