Panoramas from Partially Blurred Video

  • Jani Boutellier
  • Olli Silvén
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4153)


Numerous high-quality image stitching algorithms have been published in the recent years. Mosaics created by these methods are of high quality if the input images are not distorted. However, if the source images are blurred, parts of the resulting mosaic will be blurred also. In this paper we propose a method to create high-quality panoramas from video sequences that contain also low-quality frames. Moreover, our method is computationally efficient, which makes it attractive for hand-held devices. The algorithm uses motion detection to display correctly moving objects in the sequence. The colors of the mosaic are also balanced to handle changes in camera exposure times.


Video Sequence IEEE Computer Society Motion Detection Motion Blur Manifold Projection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Li, J.S., Randhawa, S.: Improved video mosaic construction by selecting a suitable subset of video images. In: CRPIT 2004: Proceedings of the 27th conference on Australasian computer science, Darlinghurst, pp. 143–149. Australian Computer Society, Inc., Australia (2004)Google Scholar
  2. 2.
    Hsu, C.T., Cheng, T.H., Beuker, R.A., Horng, J.K.: Feature-based video mosaic. In: Proceedings of the International Conference on Image Processing, Vancouver, Canada, vol. 2, pp. 887–890 (2000)Google Scholar
  3. 3.
    Davis, J.: Mosaics of scenes with moving objects. In: CVPR 1998: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 354–360. IEEE Computer Society Press, Washington (1998)Google Scholar
  4. 4.
    Zhu, Z., Xu, G., Riseman, E., Hanson, A.: Fast generation of dynamic and multi-resolution 360 degrees panorama from video sequences. In: Proceedings of the IEEE International Conference on Multimedia Computing and Systems, Florence, Italy, vol. 1, pp. 400–406 (1999)Google Scholar
  5. 5.
    Zitová, B., Flusser, J.: Image registration methods: a survey. Image and Vision Computing 21(11), 977–1000 (2003)CrossRefGoogle Scholar
  6. 6.
    Radke, R.J., Andra, S., Al-Kofahi, O., Roysam, B.: Image change detection algorithms: a systematic survey. IEEE Transactions on Image Processing 14(3), 294–307 (2005)CrossRefMathSciNetGoogle Scholar
  7. 7.
    Zomet, A., Levin, A., Peleg, S., Weiss, Y.: Seamless image stitching by minimizing false edges. IEEE Transactions on Image Processing 15(4), 969–977 (2006)CrossRefGoogle Scholar
  8. 8.
    Szeliski, R.: Video mosaics for virtual environments. IEEE Computer Graphics & Applications, 22–30 (1996)Google Scholar
  9. 9.
    Xiao, F., Wu, H.Z., Xiao, L., Tang, Y., Ma, W.J.: Auto method for ambient light independent panorama mosaics. In: Proceedings of International Conference on Machine Learning and Cybernetics, Shanghai, China, vol. 6, pp. 3851–3854. IEEE Computer Society Press, Los Alamitos (2004)Google Scholar
  10. 10.
    Vandewalle, P., Süsstrunk, S., Vetterli, M.: A Frequency Domain Approach to Registration of Aliased Images with Application to Super-Resolution. EURASIP Journal on Applied Signal Processing (special issue on Super-resolution) (2005)Google Scholar
  11. 11.
    Marzotto, R., Fusiello, A., Murino, V.: High resolution video mosaicing with global alignment. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 01, pp. 692–698. IEEE Computer Society Press, Los Alamitos (2004)Google Scholar
  12. 12.
    Peleg, S., Herman, J.: Panoramic mosaics by manifold projection. In: CVPR 1997: Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR 1997), Washington, DC, USA, pp. 338–343. IEEE Computer Society Press, Los Alamitos (1997)Google Scholar
  13. 13.
    Heikkilä, M., Pietikäinen, M.: An image mosaicing module for wide-area surveillance. In: VSSN 2005: Proceedings of the third ACM international workshop on Video surveillance & sensor networks, pp. 11–18. ACM Press, New York (2005)CrossRefGoogle Scholar
  14. 14.
    Bovik, A., Gibson, J., Bovik, A. (eds.): Handbook of Image and Video Processing. Academic Press, Inc., Orlando (2000)MATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jani Boutellier
    • 1
  • Olli Silvén
    • 1
  1. 1.Machine Vision Group, Department of Electrical and Information EngineeringUniversity of OuluFinland

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