[POSTER] Exploiting Photogrammetric Targets for Industrial AR

Abstract

In this work, we encourage the idea of using Photogrammetric targets for object tracking in Industrial Augmented Reality (IAR). Photogrammetric targets, especially uncoded circular targets, are widely used in the industry to perform 3D surface measurements. Therefore, an AR solution based on the uncoded circular targets can improve the work flow integration by reusing existing targets and saving time. These circular targets do not have coded patterns to establish unique 2D-3D correspondences between the targets on the model and their image projections. We solve this particular problem of 2D-3D correspondence of non-coplanar circular targets from a single image. We introduce a Conic pair descriptor, which computes the Eucledian invariants from circular targets in the model space and in the image space. A three stage method is used to compare the descriptors and compute the correspondences with up to 100% precision and 89% recall rates. We are able to achieve tracking performance of 3 FPS (2560x1920 pix) to 8 FPS (640×480 pix) depending on the camera resolution and the targets present in the scene.