An Industrial Augmented Reality Solution For Discrepancy Check

  • Authors:

  • Pierre Georgel;Pierre Schroeder;Selim Benhimane;Stefan Hinterstoisser;Mirko Appel;Nassir Navab

  • Affiliations:

  • Chair for Computer Aided Medical Procedures and Augmented Reality, TUM Munich. e-mail: georgel@in.tum.de;Chair for Computer Aided Medical Procedures and Augmented Reality, TUM Munich;Chair for Computer Aided Medical Procedures and Augmented Reality, TUM Munich;Chair for Computer Aided Medical Procedures and Augmented Reality, TUM Munich;Siemens CT, Munich, Germany. e-mail: mirko.appel@siemens.com;Chair for Computer Aided Medical Procedures and Augmented Reality, TUM Munich

  • Venue:
  • ISMAR '07 Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality
  • Year:
  • 2007

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Abstract

Construction companies employ CAD software during the planning phase, but what is finally built often does not match the original plan. The procedure of validating the model is called "discrepancy check". The system proposed here allows the user to easily obtain an augmentation in order to find differences between the planned 3D model and the built items. The main difference to previous body of work in this field is the emphasis on usability and acceptance of the solution. While standard image-based solutions use markers or rely on a "perfect" 3D model to find the pose of the camera, our software uses Anchor-Plates. Anchor-Plates are rectangular structures installed on walls and ceiling in the majority of industrial edifices. We are using them as landmarks because they are the most reliable components often used as reference coordinates by constructors. Furthermore, for real industrial applications, they are the most suitable solutions in terms of general applicability. Unfortunately, they have not been designed with Computer Vision applications in mind. On the contrary, they are often made or painted in such way that they are not easily popping out. They are therefore difficult targets to segment and to track. This paper proposes a solution to extract and match them to their 3D counterparts. We created a software that uses the detected structures for pose estimation and image augmentation. The software has been successfully employed to find discrepancies in several rooms of two industrial plants.