“Capturing and viewing gigapixel images” by Kopf, Uyttendaele, Deussen and Cohen

  • ©Johannes Kopf, Matt Uyttendaele, Oliver Deussen, and Michael F. Cohen




    Capturing and viewing gigapixel images



    We present a system to capture and view “Gigapixel images”: very high resolution, high dynamic range, and wide angle imagery consisting of several billion pixels each. A specialized camera mount, in combination with an automated pipeline for alignment, exposure compensation, and stitching, provide the means to acquire Gigapixel images with a standard camera and lens. More importantly, our novel viewer enables exploration of such images at interactive rates over a network, while dynamically and smoothly interpolating the projection between perspective and curved projections, and simultaneously modifying the tone-mapping to ensure an optimal view of the portion of the scene being viewed.


    1. Agarwala, A., Dontcheva, M., Agrawala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M. 2004. Interactive digital photomontage. ACM Transactions on Graphics 23, 3 (Proc. SIGGRAPH 2004), 294–302. Google ScholarDigital Library
    2. Brown, M., Szeliski, R., and Winder, S. 2005. Multi-image matching using multi-scale oriented patches. Proceedings of CVPR 2005, 510–517. Google ScholarDigital Library
    3. Burt, P. J., and Adelson, E. H. 1983. The Laplacian pyramid as a compact image code. IEEE Transactions on Communications COM-31, 4, 532–540.Google ScholarCross Ref
    4. Chen, S. E. 1995. QuickTime VR – an image-based approach to virtual environment navigation. Proceedings of SIGGRAPH ’95, 29–38. Google ScholarDigital Library
    5. Debevec, P. E., and Malik, J. 1997. Recovering high dynamic range radiance maps from photographs. Proceedings of SIGGRAPH 97 (August). Google ScholarDigital Library
    6. Durand, F., and Dorsey, J. 2002. Fast bilateral filtering for the display of high-dynamic-range images. ACM Transactions on Graphics 21, 3 (Proc. SIGGRAPH 2002), 257–266. Google ScholarDigital Library
    7. Eden, A., Uyttendaele, M., and Szeliski, R. 2006. Seamless image stitching of scenes with large motions and exposure differences. Proceedings of CVPR 2006) 3, 2498–2505. Google ScholarDigital Library
    8. Fattal, R., Lischinski, D., and Werman, M. 2002. Gradient domain high dynamic range compression. ACM Transactions on Graphics 21, 3 (Proc. SIGGRAPH 2002), 249–256. Google ScholarDigital Library
    9. Fischler, M. A., and Bolles, R. C. 1981. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM 24, 6, 381–395. Google ScholarDigital Library
    10. HDP, 2006. Hd photo. Microsoft Corporation, http://www.microsoft.com/whdc/xps/wmphoto.mspx.Google Scholar
    11. Kopf, J., Cohen, M., Lischinski, D., and Uyttendaele, M. 2007. Joint bilateral upsampling. ACM Transactions on Graphics 26, 3 (Proc. of SIGGRAPH 2007). Google ScholarDigital Library
    12. Lam, K. 1985. Metamerism and Colour Constancy. PhD thesis, University of Bradford.Google Scholar
    13. Lischinski, D., Farbman, Z., Uyttendaele, M., and Szeliski, R. 2006. Interactive local adjustment of tonal values. ACM Transactions on Graphics 25, 3 (Proc. SIGGRAPH 2006), 646–653. Google ScholarDigital Library
    14. Lowe, D. 2004. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 60, 2, 91–100. Google ScholarDigital Library
    15. Mitsunaga, T., and Nayar, S. 1999. Radiometric self calibration. Proceedings of CVPR ’99 2, 374–380.Google Scholar
    16. Pérez, P., Gangnet, M., and Blake, A. 2003. Poisson image editing. ACM Transactions on Graphics 22, 3 (Proc. SIGGRAPH 2003), 313–318. Google ScholarDigital Library
    17. Reinhard, E., Stark, M., Shirley, P., and Ferwerda, J. 2002. Photographic tone reproduction for digital images. ACM Transactions on Graphics 21, 3 (Proc. SIGGRAPH 2002), 267–276. Google ScholarDigital Library
    18. Reinhard, E. 2002. Parameter estimation for photographic tone reproduction. Journal of Graphics Tools 7, 1, 45–52. Google ScholarDigital Library
    19. Szeliski, R., and Kang, S. B. 1994. Recovering 3D shape and motion from image streams using nonlinear least squares. Journal of Visual Communication and Image Representation 5, 1 (March), 10–28.Google ScholarCross Ref
    20. Szeliski, R. 2006. Image alignment and stitching: A tutorial. Foundations and Trends in Computer Graphics and Computer Vision 2, 1. Google ScholarDigital Library
    21. Wilburn, B., Joshi, N., Vaish, V., Talvala, E.-V., Antunez, E., Barth, A., Adams, A., Horowitz, M., and Levoy, M. 2005. High performance imaging using large camera arrays. ACM Transactions on Graphics 24, 3 (Proc. SIGGRAPH 2005), 795–802. Google ScholarDigital Library

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