skip to main content
10.1145/2856400.2856416acmconferencesArticle/Chapter ViewAbstractPublication Pagesi3dConference Proceedingsconference-collections
research-article

Augmented reality instruction for object assembly based on markerless tracking

Published:27 February 2016Publication History

ABSTRACT

Conventional object assembly instructions are usually written or illustrated in a paper manual. Users have to associate these static instructions with real objects in 3D space. In this paper, a novel augmented reality system is presented for a user to interact with objects and instructions. While most related methods pasted obvious markers onto objects for tracking and constrained their orientations or shapes, we adopt a markerless strategy for more intuitive interaction. Based on live information from an off-the-shelf RGB-D camera, the proposed tracking procedure identifies components in a scene, tracks their 3D positions and orientations, and evaluates whether there are combinations of components. According to the detected events and poses, our indication procedure then dynamically displays indication lines, circular arrows and other hints to guide a user to manipulate the components into correct poses. The experiment shows that the proposed system can robustly track the components and respond intuitive instructions at an interactive rate. Most of users in evaluation are interested and willing to use this novel technique for object assembly.

Skip Supplemental Material Section

Supplemental Material

p95-wu.mp4

mp4

45.9 MB

References

  1. Alvarez, H., Aguinaga, I., and Borro, D. 2011. Providing guidance for maintenance operations using automatic markerless augmented reality system. In Proc. IEEE Intl. Symp. Mixed and Augmented Reality, 181--190. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. ASUSTek Computer Inc. Xtion pro live. https://www.asus.com/3D-Sensor/Xtion_PRO/.Google ScholarGoogle Scholar
  3. Autodesk Inc. 123d catch. http://www.123dapp.com/catch.Google ScholarGoogle Scholar
  4. Avrahami, D., Wobbrock, J. O., and Izadi, S. 2011. Portico: tangible interaction on and around a tablet. In Proc. ACM Symp. User Interface Software and Technology, 347--356. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Besl, P. J., and McKay, N. D. 1992. A method for registration of 3-D shapes. IEEE Trans. Pattern Analysis and Machine Intelligence 14, 2, 239--256. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Douadi, L., Aldon, M.-J., and Crosnier, A. 2006. Pair-wise registration of 3d/color data sets with icp. In Proc. IEEE/RSJ Intl. Conf. Intelligent Robots and Systems, 663--668.Google ScholarGoogle Scholar
  7. Gupta, A., Fox, D., Curless, B., and Cohen, M. 2012. DuploTrack: a real-time system for authoring and guiding duplo block assembly. In Proc. ACM Symp. User Interface Software and Technology, 389--402. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Held, R. T., Gupta, A., Curless, B., and Agrawala, M. 2012. 3D puppetry: a kinect-based interface for 3D animation. In Proc. ACM Symp. User Interface Software and Technology, 423--433. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Henderson, S., and Feiner, S. 2011. Exploring the benefits of augmented reality documentation for maintenance and repair. IEEE Trans. Visualization and Computer Graphics 17, 10, 1355--1368. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Henderson, S., and Feiner, S. K. 2011. Augmented reality in the psychomotor phase of a procedural task. In Proc. IEEE Intl. Symp. Mixed and Augmented Reality, 191--200. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Hinterstoisser, S., Cagniart, C., Ilic, S., Sturm, P., Navab, N., Fua, P., and Lepetit, V. 2012. Gradient response maps for real-time detection of textureless objects. IEEE Trans. Pattern Analysis and Machine Intelligence 34, 5, 876--888. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Hinterstoisser, S., Lepetit, V., Ilic, S., Holzer, S., Bradski, G., Konolige, K., and Navab, N. 2012. Model based training, detection and pose estimation of texture-less 3d objects in heavily cluttered scenes. In Proc. Asian Conf. Computer Vision, vol. 7724, 548--562. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Kapadia, M., Falk, J., Zünd, F., Marti, M., and Gross, M. 2015. Computer-assisted authoring of interactive narratives. In Proc. ACM SIGGRAPH Symp. Interactive 3D Graphics and Games, 85--92. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Khuong, B. M., Kiyokawa, K., Miller, A., LaViola Jr., J. J., Mashita, T., and Takemura, H. 2014. The effectiveness of an ar-based context-aware assembly support system in object assembly. In Proc. IEEE Virtual Reality, 57--62.Google ScholarGoogle Scholar
  15. Kyriazis, N., and Argyros, A. 2013. Physically plausible 3d scene tracking: The single actor hypothesis. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, 9--16. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Li, W., Agrawala, M., Curless, B., and Salesin, D. 2008. Automated generation of interactive 3d exploded view diagrams. ACM Trans. Graphics 27, 3, 101:1--101:7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Liang, R. H., Cheng, K. Y., Chan, L., Peng, C. X., Chen, M. Y., Liang, R. H., Yang, D. N., and Chen, B. Y. 2013. Gaussbits: magnetic tangible bits for portable and occlusion-free near-surface interactions. In Proc. SIGCHI Conf. Human Factors in Computing Systems, 1391--1400. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Lowe, D. G. 2004. Distinctive image features from scale-invariant keypoints. Intl J. Computer Vision 60, 91--110. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Men, H., Gebre, B., and Pochiraju, K. 2011. Color point cloud registration with 4d icp algorithm. In Proc. IEEE Intl. Conf. Robotics and Automation, 1511--1516.Google ScholarGoogle Scholar
  20. Oculus VR. Oculus rift. https://www.oculus.com/.Google ScholarGoogle Scholar
  21. Reiners, D., Stricker, D., Klinker, G., and Müller, S. 1998. Augmented reality for construction tasks: doorlock assembly. In Proc. Intl. Workshop on Augmented reality, 31--46. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Ren, Z., Mehra, R., Coposky, J., and Lin, M. C. 2012. Tabletop ensemble: touch-enabled virtual percussion instruments. In Proc. ACM SIGGRAPH Symp. Interactive 3D Graphics and Games, 7--14. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Tang, A., Owen, C., Biocca, F., and Mou, W. 2003. Comparative effectiveness of augmented reality in object assembly. In Proc. SIGCHI Conf. Human Factors in Computing Systems, 73--80. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Yang, J., Li, H., and Jia, Y. 2013. Go-icp: Solving 3d registration efficiently and globally optimally. In Proc. IEEE Intl. Conf. Computer Vision, 1457--1464. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Zauner, J., Haller, M., Brandl, A., and Hartman, W. 2003. Authoring of a mixed reality assembly instructor for hierarchical structures. In Proc. IEEE/ACM Intl. Symp. Mixed and Augmented Reality, 237--246. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Augmented reality instruction for object assembly based on markerless tracking

        Recommendations

        Comments

        Login options

        Check if you have access through your login credentials or your institution to get full access on this article.

        Sign in
        • Published in

          cover image ACM Conferences
          I3D '16: Proceedings of the 20th ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
          February 2016
          200 pages
          ISBN:9781450340434
          DOI:10.1145/2856400

          Copyright © 2016 ACM

          Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

          Publisher

          Association for Computing Machinery

          New York, NY, United States

          Publication History

          • Published: 27 February 2016

          Permissions

          Request permissions about this article.

          Request Permissions

          Check for updates

          Qualifiers

          • research-article

          Acceptance Rates

          Overall Acceptance Rate148of485submissions,31%

        PDF Format

        View or Download as a PDF file.

        PDF

        eReader

        View online with eReader.

        eReader