An Indoor Mobile Visual Localization Algorithm Based On Harris-Sift

Abstract

Abstract Through the installation of a monocular vision sensor on a target and shooting sequence images of the floor, combined with the characteristics of the sequence images, an indoor mobile visual localization algorithm based on Hams-SIFT is proposed. The algorithm is first to establish first-order DOG scale space of sequence images of the floor, to extract feature points in each layer images of DOG scale space by using Hams operator, then to select scale-invariant feature points to calculate each feature point descriptor and match, and thus to depict the trajectory of the movement of the target to achieve positioning. Using several different indoor sequence images under the different environment respectively, the algorithm is verified, positioning experimental results show the effectiveness of the algorithm.