Research on binocular ranging method based on feature point extraction and matching

Abstract

At present, artificial intelligence has become a hot topic, and the development of its related fields is also developing rapidly, among which visual ranging and image processing are particularly important for the development of artificial intelligence. Now there are many ranging methods are not fast enough, and measurement accuracy is not high, leading to the resulting estimates there are large deviation distance and the actual distance, such as unmanned vehicle, unmanned aircraft in operation process, cannot be accurately driving distance and obstacle avoidance, and existing deviations in robot grab, which cause personnel life safety is threatened, economic property damage. In order to solve the above related problems, this paper uses SIFT algorithm and ORB algorithm to extract feature points, and then through BFmatcher, FlannBasedMatcher, KnnMatch to match, finally get the corresponding distance, from the algorithm and accuracy of the two aspects of relevant research. It is concluded from the experimental measurement that FlannBasedMatcher takes into account both speed and accuracy after SIFT algorithm extraction, while ORB algorithm is faster than SIFT algorithm.