Projector-Based Augmented Reality for Quality Inspection Of Scanned Objects

Abstract

After scanning or reconstructing the geometry of objects, we need to inspect the result of our work. Are there any parts missing? Is every detail covered in the desired quality? We typically do this by looking at the resulting point clouds or meshes of our objects on-screen. What, if we could see the information directly visualized on the object itself? Augmented reality is the generic term for bringing virtual information into our real environment. In our paper, we show how we can project any 3D information like thematic visualizations or specific monitoring information with reference to our object onto the object’s surface itself, thus augmenting it with additional information. For small objects that could for instance be scanned in a laboratory, we propose a low-cost method involving a projector-camera system to solve this task. The user only needs a calibration board with coded fiducial markers to calibrate the system and to estimate the projector’s pose later on for projecting textures with information onto the object’s surface. Changes within the projected 3D information or of the projector’s pose will be applied in real-time. Our results clearly reveal that such a simple setup will deliver a good quality of the augmented information.

Marker-Based Localization of the Microsoft Hololens in Building Models

“…Hübner et al (2018) evaluate such ArUco markers for tracking of relative poses. Kern et al (2017) use a pattern of ArUco markers for precise pose estimation of a projector-camera-system for AR. Koch et al (2012) use natural markers that are already available in the building like device IDs, exit signs or position marks of fire extinguishers.…”

Comparison of Uni- and Multimodal Interfaces for Spatial Human-Robot Interaction

“…To further optimize projection matching accuracy, an initial calibration refinement optimizes the extrinsic parameters of the projector-camera system given a precisely known pose of a 3D object [23]. A depth buffer-based mask removes interfering seams at the object border by applying a morphological erosion on the object silhouette [36]. Figure 5 shows the appearance of a highlighted weld using the real workpiece.…”

Assessing the Value of Multimodal Interfaces: A Study on Human–Machine Interaction in Weld Inspection Workstations

“…To further optimize projection matching accuracy, an initial calibration refinement optimizes the extrinsic parameters of the projector-camera system given the precisely known pose of a 3D object [25]. A depth buffer-based mask removes interfering seams at the object border by applying a morphological erosion on the object silhouette [38]. Figure 5 shows the appearance of a highlighted weld using the real workpiece.…”