The inter-frame feature matching and tracking of binocular vision based on the ORB-PyrLK algorithm

The feature matching and tracking of binocular vision inter-frame images have been divided into three parts in this paper. Before image feature extraction, an image binarization segmentation method based on HSV color space is used to extract the target in order to reduce the searching range of feature points and improve the matching efficiency. About feature matching, a modified ORB method combining KNN rough algorithm and RANSAC fine algorithm is applied to improve the matching accuracy of left-right frame images. As to feature tracking which can be seen as the matching of front-rear frames, an inter-frame matching method based on ORB feature optical flow is proposed to realize the aim. Results are shown in several experiments to demonstrate that the proposed algorithm can improve the accuracy and efficiency of left-right frame and front-rear frame image matching.