Skip to main content
SpringerLink
Log in

Automatic Panoramic Image Stitching using Invariant Features

  • Published:
International Journal of Computer Vision Aims and scope Submit manuscript

Abstract

This paper concerns the problem of fully automated panoramic image stitching. Though the 1D problem (single axis of rotation) is well studied, 2D or multi-row stitching is more difficult. Previous approaches have used human input or restrictions on the image sequence in order to establish matching images. In this work, we formulate stitching as a multi-image matching problem, and use invariant local features to find matches between all of the images. Because of this our method is insensitive to the ordering, orientation, scale and illumination of the input images. It is also insensitive to noise images that are not part of a panorama, and can recognise multiple panoramas in an unordered image dataset. In addition to providing more detail, this paper extends our previous work in the area (Brown and Lowe, 2003) by introducing gain compensation and automatic straightening steps.

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

Similar content being viewed by others

References

  • Agarwala, A., Dontcheva, M., Agarwala, M., Drucker, S., Colburn, A., Curless, B., Salesin, D., and Cohen, M. 2004. Interactive digital photomontage. In ACM Transactions on Graphics (SIGGRAPH'04).

  • Burt, P. and Adelson, E. 1983. A multiresolution spline with application to image mosaics. ACM Transactions on Graphics, 2(4):217–236.

    Article  Google Scholar 

  • Bascle, B., Blake, A., and Zisserman, A. 1996. Motion deblurring and super-resolution from and image sequence. In Proceedings of the 4th European Conference on Computer Vision (ECCV96). Springer-Verlag, pp. 312–320.

  • Beis, J. and Lowe, D. 1997. Shape indexing using approximate nearest-neighbor search in high-dimensional spaces. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR97). pp. 1000–1006.

  • Brown, M. and Lowe, D. 2003. Recognising panoramas. In Proceedings of the 9th International Conference on Computer Vision (ICCV03). Nice, vol. 2, pp. 1218–1225.

  • Brown, D. 1971. Close-range camera calibration. Photogrammetric Engineering. 37(8):855–866.

    Google Scholar 

  • Brown, M., Szeliski, R., and Winder, S. 2005. Multi-image matching using multi-scale oriented patches. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR05). San Diego.

  • Chen, S. 1995. Quick Time VR–-An image-based approach to virtual environment navigation. In SIGGRAPH'95. vol. 29, pp. 29–38.

  • Capel, D. and Zisserman, A. 1998. Automated mosaicing with super-resolution zoom. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR98). pp. 885–891.

  • Davis, J. 1998. Mosaics of scenes with moving objects. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR98). pp. 354–360.

  • Debevec, P. and Malik, J. 1997. Recovering high dynamic range radiance maps from photographs. Computer Graphics. 31:369–378.

    Google Scholar 

  • Fischler, M. and Bolles, R. 1981. Random sample consensus: A paradigm for model fitting with application to image analysis and automated cartography. Communications of the ACM. 24:381–395.

    Article  MathSciNet  Google Scholar 

  • Goldman, D.B. and Chen, J.H. 2005 Vignette and exposure calibation and compensation. In Proceedings of the 10th International Conference on Computer Vision (ICCV05). pp. I:899–906.

  • Harris, C. 1992. Geometry from visual motion. In Blake, A. and Yuille, A., (eds.), Active Vision. MIT Press, pp. 263–284.

  • Huber P.J. 1981. Robust Statistics. Wiley.

  • Hartley, R. and Zisserman, A. 2004. Multiple View Geometry in Computer Vision. 2nd edn. Cambridge University Press, ISBN: 0521540518.

  • Irani, M. and Anandan, P. 1999. About direct methods. In Triggs, B., Zisserman, A., and Szeliski, R. (eds.), Vision Algorithms: Theory and Practice. number 1883 in LNCS. Springer-Verlag, Corfu, Greece, pp. 267–277.

    Google Scholar 

  • Lowe, D. 2004. Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision. 60(2):91–110.

    Article  Google Scholar 

  • Meehan, J. 1990. Panoramic Photography. Amphoto Books.

  • Milgram, D. 1975. Computer methods for creating photomosaics. IEEE Transactions on Computers. C-24 (11):1113–1119.

    Google Scholar 

  • McLauchlan, P. and Jaenicke, A. 2002. Image mosaicing using sequential bundle adjustment. Image and Vision Computing. 20(9–10):751–759.

    Article  Google Scholar 

  • Microsoft Digital Image Pro. http://www.microsoft.com/products/imaging.

  • Rother, C. and Carlsson, S. 2002. Linear multi view reconstruction and camera recovery using a reference plane. International Journal of Computer Vision. 49(2/3):117–141.

    Article  MATH  Google Scholar 

  • Realviz. http://www.realviz.com.

  • Seetzen, H., Heidrich, W., Stuerzlinger, W., Ward, G., Whitehead, L., Trentacoste, M., Ghosh, A., and Vorozcovs, A. 2004. High dynamic range display systems. In ACM Transactions on Graphics (SIGGRAPH'04).

  • Szeliski, R. and Kang, S. 1995. Direct methods for visual scene reconstruction. In IEEE Workshop on Representations of Visual Scenes. Cambridge, MA, pp. 26–33.

  • Sawhney, H. and Kumar, R. 1999. True multi-image alignment and its application to mosaicing and lens distortion correction. IEEE Transactios on Pattern Analysis and Machine Intelligence. 21(3):235–243.

    Article  Google Scholar 

  • Szeliski, R. and Shum, H. 1997. Creating full view panoramic image mosaics and environment maps. Computer Graphics (SIGGRAPH'97). 31(Annual Conference Series):251–258.

  • Shum, H. and Szeliski, R. 2000. Construction of panoramic mosaics with global and local alignment. International Journal of Computer Vision. 36(2):101–130.

    Article  Google Scholar 

  • Shi, J. and Tomasi, C. 1994. Good features to track. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR94). Seattle.

  • Sivic, J. and Zisserman, A. 2003. Video Google: A text retrieval approach to object matching in videos. In Proceedings of the 9th International Conference on Computer Vision (ICCV03).

  • Szeliski, R. 2004. Image alignment and stitching: A tutorial. Technical Report MSR-TR-2004-92, Microsoft Research.

  • Triggs, W., McLauchlan, P., Hartley, R., and Fitzgibbon, A. 1999. Bundle adjustment: A modern synthesis. In Vision Algorithms: Theory and Practice. number 1883 in LNCS. Springer-Verlag. Corfu, Greece, pp. 298–373.

    Google Scholar 

  • Torr, P. 2002. Bayesian model estimation and selection for epipolar geometry and generic manifold fitting. International Journal of Computer Vision. 50(1):35–61.

    Article  MATH  Google Scholar 

  • Uyttendaele, M., Eden, A., and Szeliski, R. 2001. Eliminating ghosting and exposure artifacts in image mosaics. In Proceedings of the Interational Conference on Computer Vision and Pattern Recognition (CVPR01). Kauai, Hawaii, vol. 2, pp. 509–516.

  • Zoghlami, I., Faugeras, O., and Deriche, R. 1997. Using geometric corners to build a 2D mosaic from a set of images. In Proceedings of the International Conference on Computer Vision and Pattern Recognition, Puerto Rico. IEEE.

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of British Columbia, Vancouver, Canada

    Matthew Brown & David G. Lowe

Authors
  1. Matthew Brown
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. David G. Lowe
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matthew Brown.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brown, M., Lowe, D.G. Automatic Panoramic Image Stitching using Invariant Features. Int J Comput Vision 74, 59–73 (2007). https://doi.org/10.1007/s11263-006-0002-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11263-006-0002-3

Keywords

Search

Navigation