A fast object registration method for augmented reality assembly with simultaneous determination of multiple 2D-3D correspondences

Abstract

Abstract A fast and robust object registration is one of the fundamental steps of an augmented reality (AR) assembly guidance system. To manage the registration of texture-less objects from monocular images, this paper presents a three-dimensional (3D) object registration solution in the view-based framework, which incorporates a new image feature named as chain-of-lines feature (COLF). The COLF, constructed by several directed line segments with geometric constraints, enhances the robustness of the registration by establishing multiple correspondences between the two-dimensional (2D) image and 3D model simultaneously. In order to save on computational cost and improve the efficiency of the COLF-based registration, a compression algorithm based on the local breadth-first search (LBFS) strategy is also proposed; this adaptively reduces the number of keyframes according to the target model. In the experimental evaluation, the combination of COLF and LBFS-based keyframe compression shows higher registration success rate and faster speed in comparison with conventional registration methods. Moreover, an AR assembly guidance prototype system for reductors is introduced to illustrate the application of the proposed registration method.