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Video Mosaicing Based on Structure from Motion for Distortion-Free Document Digitization

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Book cover Computer Vision – ACCV 2007 (ACCV 2007)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4844))

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Abstract

This paper presents a novel video mosaicing method capable of generating a geometric distortion-free mosaic image using a hand-held camera. For a document composed of curved pages, mosaic images of virtually flattened pages are generated. The process of our method is composed of two stages : real-time stage and off-line stage. In the real-time stage, image features are automatically tracked on the input images, and the viewpoint of each image as well as the 3-D position of each image feature are estimated by a structure-from-motion technique. In the off-line stage, the estimated viewpoint and 3-D position of each feature are refined and utilized to generate a geometric distortion-free mosaic image. We demonstrate our prototype system on curved documents to show the feasibility of our approach.

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References

  1. Szeliski, R.: Image Mosaicing for Tele-Reality Applications. In: Proc. IEEE Workshop on Applications of Computer Vision, pp. 230–236. IEEE Computer Society Press, Los Alamitos (1994)

    Google Scholar 

  2. Capel, D., Zisserman, A.: Automated Mosaicing with Super-resolution Zoom. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pp. 885–891. IEEE Computer Society Press, Los Alamitos (1998)

    Google Scholar 

  3. Chiba, N., Kano, H., Higashihara, M., Yasuda, M., Osumi, M.: Feature-based Image Mosaicing. In: Proc. IAPR Workshop on Machine Vision Applications, pp. 5–10 (1998)

    Google Scholar 

  4. Hsu, C.T., Cheng, T.H., Beuker, R.A., Hong, J.K.: Feature-based Video Mosaicing. In: Proc. IEEE Int. Conf. on Image Processing, vol. 2, pp. 887–890. IEEE Computer Society Press, Los Alamitos (2000)

    Google Scholar 

  5. Lhuillier, M., Quan, L., Shum, H., Tsui, H.T.: Relief Mosaicing by Joint View Triangulation. In: IEEE Int. Conf. on Computer Vision and Pattern Recognition, vol. 1, pp. 785–790. IEEE Computer Society Press, Los Alamitos (2001)

    Google Scholar 

  6. Takeuchi, S., Shibuichi, D., Terashima, N., Tominage, H.: Adaptive Resolution Image Acquisition Using Image Mosaicing Technique from Video Sequence. In: Proc. IEEE Int. Conf. on Image Processing, vol. 1, pp. 220–223. IEEE Computer Society Press, Los Alamitos (2000)

    Google Scholar 

  7. Cao, H., Ding, X., Liu, C.: A Cylindrical Surface Model to Rectify the Bound Document Image. In: Proc. Int. Conf. on Computer Vision, vol. 1, pp. 228–233 (2003)

    Google Scholar 

  8. Brown, M.S., Tsoi, Y.C.: Undistorting Imaged Print Materials using Boundary Information. In: Proc. Asian Conf. on Computer Vision, vol. 1, pp. 551–556 (2004)

    Google Scholar 

  9. Sato, T., Kanbara, M., Yokoya, N., Takemura, H.: Dense 3-D Reconstruction of an Outdoor Scene by Hundreds-baseline Stereo Using a Hand-held Video Camera. Int. J. of Computer Vision 47(1-3), 119–129 (2002)

    Article  MATH  Google Scholar 

  10. Harris, C., Stephens, M.: A Combined Corner and Edge Detector. In: Proc. Alvey Vision Conf., pp. 147–151 (1988)

    Google Scholar 

  11. Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. In: Communications of the ACM, vol. 24(6), pp. 381–395. ACM Press, New York (1981)

    Google Scholar 

  12. Triggs, B., McLauchlan, P., Hartley, R., Fitzgibbon, A.: Bundle Adjustment a Modern Synthesis. In: Proc. Int. Workshop on Vision Algorithms, pp. 298–372 (1999)

    Google Scholar 

  13. Kanatani, K.: Geometric Information Criterion for Model Selection. Int. J. of Computer Vision 26(3), 171–189 (1998)

    Article  Google Scholar 

  14. Tsai, R.Y.: An Efficient and Accurate Camera Calibration Technique for 3D Machine Vision. In: Proc. IEEE Conf. on Computer Vision and Pattern Recognition, pp. 364–374. IEEE Computer Society Press, Los Alamitos (1986)

    Google Scholar 

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Yasushi Yagi Sing Bing Kang In So Kweon Hongbin Zha

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© 2007 Springer-Verlag Berlin Heidelberg

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Iketani, A., Sato, T., Ikeda, S., Kanbara, M., Nakajima, N., Yokoya, N. (2007). Video Mosaicing Based on Structure from Motion for Distortion-Free Document Digitization. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds) Computer Vision – ACCV 2007. ACCV 2007. Lecture Notes in Computer Science, vol 4844. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-76390-1_8

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  • DOI: https://doi.org/10.1007/978-3-540-76390-1_8

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-76389-5

  • Online ISBN: 978-3-540-76390-1

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