Skip to main content
Log in

Content-aware disparity adjustment for different stereo displays

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

Abstract

In this paper, we present an effective disparity mapping method for binocular stereoscopic image. It is inspired by the observation that its displayed depth would change, when a stereoscopic image is displayed on different size screens. The phenomenon may bring an uncomfortable experience for viewers. To make a comfortable stereoscopic image for viewers, moreover to adapt a stereoscopic image to a target display screen, we propose a content-aware disparity adjustment method. Firstly, the disparity mapping is established to control and retarget the depth of a stereoscopic scene. Then, the relationship between the disparity editing and image content editing is established to guide the proposed warping model. At last, to implement the disparity mapping operator, we propose a content-aware stereoscopic mesh warping model, which can simultaneously avoid the salient region distortion and adjust disparity to a target range by establishing the relationship. Experimental results show that the proposed method can effectively adjust disparity of stereoscopic image, which not only avoids the salient region distortion and adjusts disparity to a target range.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Basha T, Moses Y, Avidan S (2013) Stereo seam carving a geometrically consistent approach. IEEE Trans Pattern Anal Mach Intell 35(10):2513–2525

    Article  Google Scholar 

  2. Chan HM, Chung ACS, Yu SCH, Wells WM (2004) III 2D–3D vascular registration between digital subtraction angiographic (DSA) and magnetic resonance angiographic (MRA) images. IEEE Biomed Imaging Nano Macro 1:708–711

    Google Scholar 

  3. Chang CH, Liang CK, Chuang YY (2011) Content-aware display adaptation and interactive editing for stereoscopic images. IEEE Trans Multimedia 13(4):589–601

    Article  Google Scholar 

  4. Feldmann I, Scheer O, Kauff P (2003) Nonlinear depth scaling for immersive video applications. WIAMIS, London

    Book  Google Scholar 

  5. Fröhlich B, Barrass S, Zehner B, Plate J, Gobel M (1999) Exploring geo-scientific data in virtual environments. Proc IEEE Vis 99:169–173

    Google Scholar 

  6. Getty DJ, D’Orsi CJ, Pickett RM (2008) Stereoscopic digital mammography: Improved accuracy of lesion detection in breast cancer screening. Lect Notes Comput Sci 5116:74–79

    Article  Google Scholar 

  7. Goferman S, Zelnik-Manor L, Tal A (2012) Context-aware saliency detection. IEEE Trans Pattern Anal Mach Intell 34(10):1915–1926

    Article  Google Scholar 

  8. Halbfinger DM (2008) [Retrieved March 13]; with theaters barely digital, studios push 3-D. New York Times, New York

    Google Scholar 

  9. Heckbert PS (1989) Fundamentals of texture mapping and image warping. Master’s thesis, University of California, Berkeley

  10. Hirschmuller H (2008) Stereo processing by semiglobal matching and mutual information. IEEE Trans Pattern Anal Mach Intell 30(2):328–341

    Article  Google Scholar 

  11. Hoffman DM, Girshick AR, Akeley K, Banks MS (2008) Vergence-accommodation conflicts hinder visual performance and cause visual fatigue. J Vis 8(3):33, 1–30

  12. Holliman N (2002) 3D display systems. Department of Computer Science, University Durham, Durham, Technical Report

    Google Scholar 

  13. Jiang GY, Zhou JM, Yu M, Zhang Y, Shao F, Peng ZJ (2014) Binocular vision based objective quality assessment method for stereoscopic images. Multimedia Tools Appl. doi:10.1007/s11042-014-2051-x

    Google Scholar 

  14. Jung C, Wang S (2014) Visual comfort assessment in stereoscopic 3D images using salient object disparity. Electron Lett 51(6):482–484

    Article  Google Scholar 

  15. Kang K, Cao Y, Zhang J, Wang ZF (2014) Salient object detection and classification for stereoscopic images. Multimedia Tools Appl. doi:10.1007/s11042-014-2142-8

    Google Scholar 

  16. Lang M, Hornung A, Wang O, Poulakos S, Smolic A, Gross M (2010) Nonlinear disparity mapping for stereoscopic 3d. ACM Trans Graph 29(4):1–10

    Article  Google Scholar 

  17. Lin H, Guan S, Lee C, Ouhyoung M (2011) Stereoscopic 3D experience optimization using cropping and warping. In: ACM SIGGRAPH Asia Sketches. Hong Kong. doi:10.1145/2077378.2077428

  18. Liu F, Gleicher M, Jin H, Agarwala A (2009) Content-preserving warps for 3d video stabilization. ACM Trans Graph 28(3):36–44

    Google Scholar 

  19. Liu F, Niu Y, Jin H (2013) Casual stereoscopic photo authoring. IEEE Trans Multimedia 15(1):129–140

    Article  Google Scholar 

  20. Luo SJ, Shen I, Chen BY, Cheng WH, Chuang YY (2012) Perspective-aware warping for seamless stereoscopic image cloning. ACM Trans Graph 31(6):182–190

    Google Scholar 

  21. Shibata, T., Kim, J., Hoffman, D.M. & Banks, M.S. (2011) The zone of comfort: Predicting visual discomfort with stereo displays. J Vis 11(8):11, 1–29

  22. Smolic A, Kauff P, Knorr S, Hornung A (2011) Kunter: three-dimensional video postproduction and processing. Proc IEEE 99(4):607–625

    Article  Google Scholar 

  23. Wang L, Jin H, Yang R and Gong M (2008) Stereoscopic in painting: joint color and depth completion from stereo images. In: Proceedings of IEEE conference on computer vision and pattern recognition (CVPR). pp 1–8

  24. Wang YS, Tai CL, Sorkine O, Lee TY (2008) Optimized scale-and-stretch for image resizing. ACM Trans Graph 27(5):1–8

    Article  Google Scholar 

  25. Yoo JW, Yea S, Park IK (2013) Content-driven retargeting of stereoscopic images. IEEE Signal Process Lett 20(5):519–522

    Article  Google Scholar 

  26. Zitnick CL, Kang SB, Uyttendaele M, Winder S, Szeliski R (2004) High-quality video view interpolation using a layered representation. ACM Trans Graph 23(3):600–608

    Article  Google Scholar 

Download references

Acknowledgments

This work is supported by the National Natural Science Foundation of China under Grants 61471262, by Natural Science Foundation key international (regional) cooperation research projects 61520106002, and by Ph.D. Programs Foundation of Ministry of Education of China under Grants 20130032110010, by China Scholarship Council (CSC).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Weiqing Yan.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yan, W., Hou, C., Wang, B. et al. Content-aware disparity adjustment for different stereo displays. Multimed Tools Appl 76, 10465–10479 (2017). https://doi.org/10.1007/s11042-016-3442-y

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-016-3442-y

Keywords

Navigation