Skip to main content
SpringerLink
Log in

Occlusion handling using moving volume and ray casting techniques for augmented reality systems

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

Obtaining the correct occlusion relationship between real objects and virtual objects is vital for improving augmented reality technology. In this paper, we propose a novel occlusion handling method using moving volume and ray casting techniques. Our method is divided into two steps. In the first step, we obtain the volume of the corresponding physical space and arbitrarily move the volume to extend the reconstruction area. In the second step, we calculate the 3D coordinates of each pixel in the scene and re-project the rendered objects to the same 3D coordinates system. Correct occlusion relationships are obtained by comparing the z coordinates of real and virtual objects. Several experiments are performed to validate the performance of the proposed method. The experimental results indicate that our method can correctly and rapidly handle occlusion.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Breen DE, Whitaker RT, Rose E et al (1996) Interactive occlusion and automatic object placement for augmented reality. Comput Graphics Forum 15(3):11–22

    Article  Google Scholar 

  2. Dong SY, Kamat VR (2010) Resolving incorrect visual occlusion in outdoor augmented reality using TOF camera and OpenGL frame buffer. In: 10th International Conference on Construction Applications of Virtual Reality(CONVR), CONVR, Sendai, Japan, pp 55–63

  3. Du C, Chen Y-L, Ye M, Ren L (2016) Edge Snapping-Based Depth Enhancement for Dynamic Occlusion Handling in Augmented Reality. ISMAR, pp 54–62

  4. Duan LY, Guan T, Luo YW (2013) Wide area registration on camera phones for mobile augmented reality applications. Sens Rev 33(3):209–219

    Article  Google Scholar 

  5. Fischer J, Bartz D, Straßer W (2004) Occlusion handling for medical augmented reality using a volumetric phantom model. In: Proceedings of ACM Symposium on Virtual Reality Software and Technology, Hinkong, China, pp 174–177. ACM

  6. Fuhrmann A, Hesina G, Faure F et al (1999) Occlusion in collaborative augmented environments. Comput Graph 23(6):809–819

    Article  Google Scholar 

  7. Fukiage T, Oishi T, Ikeuchi K (2012) Reduction of contradictory partial occlusion in mixed reality by using characteristics of transparency perception, In: 11th IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR), Atlanta, United States, pp 129–139. IEEE

  8. GML Camera Calibration Toolbox downloads resource (2017) Available online: http://research.graphicon.ru/calibration/gml-c-camera-calibration-toolbox-5.html

  9. Wei B, Guan T, Duan L, Yu J, Mao T (2015) Wide area localization and tracking on camera phones for mobile augmented reality systems. Multimedia Systems 21(4):381–399

  10. Guan T, Wang Y, Duan L (2015) On-device mobile landmark recognition using binarized descriptor with multifeature fusion. ACM Trans Intell Syst Technol 7(1). https://doi.org/10.1145/2795234

  11. Izadi S, Kim D, Hilliges O, et al (2011) KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera. In: Proceedings of the 24th annual ACM symposium on User interface software and technology. ACM, Santa Barbara, pp 559–568

  12. Izadi S, Kim D, Hilliges O, Molyneaux D, Newcombe R, Kohli P, Shotton J, Hodges S, Freeman D, Davison A, Fitzgibbon A (2011) KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera. In Proceedings of the ACM symposium on User interface software and technology (UIST), pp 559–568

  13. Ladikos A, Navab N (2009) Real-time 3D reconstruction for occlusion-aware interactions in mixed reality. Lect Notes Comput Sci 5857:480–489

    Article  Google Scholar 

  14. Lepetit V, Berger MO (2000) A semi-automatic method for resolving occlusion in augmented reality. In: Proc. of the CVPR, Hilton Head, SC, USA, pp 225–230. IEEE

  15. Lepetit V, Berger MO (2000) Handling occlusion in augmented reality systems: a semi-automatic method. In: IEEE and ACM International Symposium on Augmented Reality (ISAR), Munich, Germany, pp 137–146. IEEE

  16. Lieberknecht S, Huber A, Ilic S, et al (2011) RGB-D camera-based parallel tracking and meshing. In: Proceedings of 10th IEEE International Symposium on Mixed and Augmented Reality. IEEE, Basel, pp 147–155

  17. Lu BV, Kakuta T, Kawakaml R, et al (2010) Foreground and shadow occlusion handling for outdoor augmented reality. In: Proceedings of the 9th IEEE International Symposium on Mixed and Augmented Reality. IEEE Computer Society Press, Los Alamitos, pp 109–118

  18. Pan H, Guan T, Luo Y (2016) Dense 3D reconstruction combining depth and RGB information. Neurocomputing 175:644–651

  19. Ong KC, Teh HC, Tan TS (1998) Resolving occlusion in image sequence made easy. Vis Comput 14(4):153–165

    Article  Google Scholar 

  20. Roth H, Vona M (2012) Moving Volume KinectFusion. In: Proceedings of British Machine Vision Conference. Guildford, pp 1–11

  21. Sanches SRR, Tokunaga DM, Silva VF, Sementille AC, Tori R (2012) Mutual occlusion between real and virtual elements in augmented reality based on fiducial markers, In: 2012 I.E. Workshop on Applications of Computer Vision (WACV), Breckenridge, USA, pp 49–54. IEEE

  22. Schmidt J, Niemann H, Vogt S (2002) Dense disparity maps in real-time with an application to augmented reality, In: Proceedings of Sixth IEEE Workshop on Applications of Computer Vision, Orlando, Florida, United States, pp 225–230. IEEE

  23. Tian Y, Guan T, Wang C (2010) An automatic occlusion handling method in augmented reality. Sens Rev 30(3):210–218

    Article  Google Scholar 

  24. Zhu JJ, Pan ZG, Sun C, Chen WZ (2010) Handling occlusions in video-based augmented reality using depth information. Comp Anim Virtual Worlds 21(5):509–521

    Article  Google Scholar 

Download references

Acknowledgements

This work is supported by the National Natural Science Foundation (No. 61605054) and National Natural Science Foundation (No. 61501199).

Author information

Authors and Affiliations

  1. School of Educational Information Technology, Central China Normal University, Room 626, Building 9, NO.152 Luoyu Road, Wuhan, Hubei, 430079, China

    Yuan Tian, Xuefan Wang, Huang Yao, Jia Chen & Zhifeng Wang

  2. School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China

    Liu Yi

Authors
  1. Yuan Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xuefan Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Huang Yao
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jia Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Zhifeng Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Liu Yi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yuan Tian.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tian, Y., Wang, X., Yao, H. et al. Occlusion handling using moving volume and ray casting techniques for augmented reality systems. Multimed Tools Appl 77, 16561–16578 (2018). https://doi.org/10.1007/s11042-017-5228-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-017-5228-2

Keywords

Search

Navigation