摘要：Abstract Early augmented reality (AR) community has paid a lot of attention to identifying 2D fiducial markers in AR scene, only a little works have been devoted to 3D objects perception. With the massively increased usage of 3D representation, it is highly desirable that powerful processing tools and algorithms should be developed for 3D recognition purpose in the augmented reality domain. In this paper, we address the 3D depth understanding problem for AR assembly applications. We propose a 3D registration based perception method designed for desk assembly environments. The 3D perception method involves two tasks: the optical flow based structure from motion (SFM) and a coplanar 4 points set registration of the SFM point cloud and CAD models point cloud. From the transformation, the position and orientation of the real industrial object in the assembly environment can be determined and an AR operation can be applied. The novelty of our method resides in that it does not require any marker attached on the scene and obtain a more accurate registration result.
