A Space-Mapping Method for Object Location Estimation Adaptive to Camera Setup Changes for Vision-Based Automation Applications

Abstract

A new space-mapping method for object location estimation, which is adaptive to camera setup changes, for use in various automation applications is proposed. The location of an object appearing in an image is estimated by mapping image coordinates of object points to corresponding real-world coordinates using a mapping table, which is constructed in two stages, with the first stage for establishing a basic table using bilinear interpolation in the camera manufacturing environment and the second for adapting the table to changes of camera heights and orientations in the application field. Analytic equations for table adaptation are derived by skillful utilization of both image formation and camera geometry properties. Good experimental results are shown to prove the feasibility of the proposed method.