Automatic Registration of Smooth Object Image to 3D CAD Model for Industrial Inspection Applications

Ser-Nam Lim, Li Guan, Shubao Liu, Xingwei Yang

Abstract: We describe an algorithmic pipeline for automatic registration of smooth object image on 3D CAD model, which has many applications in industrial inspections. This enables camera pose estimation and 3D measurement of structures of interest from 2D images. In this work, when given a query image, we leverage image retrieval to find a similar historical image, in which its 2D points' corresponding locations on the 3D model has already been computed offline. By matching features between the query and retrieved image, the latter's feature locations on the 3D model can be transferred to the former. Camera pose of the query image can then be computed for overlaying it on the 3D model. A big challenge arises when the object of interest, such as one with smooth metallic surface, has extremely limited number of reliable features, which is especially true in industrial inspection. This causes popular recognition and detection algorithms as well as 3D calibration algorithms that depend on a sufficient number of good features to fail. We describe how we construct a pipeline to overcome this challenge. Comparative results and accuracy of 3D measurements made on real datasets with the proposed pipeline validate our approach.