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Recursive Structure from Motion

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Computer Vision, Graphics, and Image Processing (ICVGIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10481))

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Abstract

In this paper we present a technique that estimates the Structure from Motion (SFM) in a recursive fashion. Traditionally successful SFM algorithms take the set of images and estimate the scene geometry and camera positions either using incremental algorithms or the global algorithms and do the refinement process [2] to reduce the reprojection error. In this work it is assumed that we don’t have complete image set at the start of the reconstruction process, unlike most of the traditional approaches present in the literature. It is assumed that the set of images come in at the regular intervals and we recursively perform the SFM on the incoming set of images and update the previously reconstructed structure with the structure estimated from the current set of images. The proposed system has been tested on two datasets which consist of 12 images and 60 images respectively and reconstructions obtained show the validity of our proposed technique.

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References

  1. Agarwal, S., Snavely, N., Simon, I., Seitz, S.M., Szeliski, R.: Building Rome in a day. In: International Conference on Computer Vision (ICCV), Kyoto, Japan (2009)

    Google Scholar 

  2. Agarwal, S., Snavely, N., Seitz, S.M., Szeliski, R.: Bundle adjustment in the large. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010. LNCS, vol. 6312, pp. 29–42. Springer, Heidelberg (2010). doi:10.1007/978-3-642-15552-9_3

    Chapter  Google Scholar 

  3. Wilson, K., Snavely, N.: Robust global translations with 1DSfM. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8691, pp. 61–75. Springer, Cham (2014). doi:10.1007/978-3-319-10578-9_5

    Google Scholar 

  4. Crandall, D., Owens, A., Snavely, N., Huttenlocher, D.P.: Discrete-continuous optimization for large-scale structure from motion. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2011)

    Google Scholar 

  5. Chatterjee, A., Govindu, V.M.: Efficient and robust large-scale rotation averaging. In: Proceedings of International Conference on Computer Vision (ICCV) (2013)

    Google Scholar 

  6. Wu, C.: Towards linear-time incremental structure from motion. In: Proceedings of the 2013 International Conference on 3D Vision (3DV 2013), pp. 127–134. IEEE Computer Society, Washington, D.C

    Google Scholar 

  7. Olsson, C., Enqvist, O.: Stable structure from motion for unordered image collections. In: Heyden, A., Kahl, F. (eds.) SCIA 2011. LNCS, vol. 6688, pp. 524–535. Springer, Heidelberg (2011). doi:10.1007/978-3-642-21227-7_49

    Chapter  Google Scholar 

  8. Enqvist, O., Kahl, F., Olsson, C.: Non-sequential structure from motion. IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 264–271 (2011)

    Google Scholar 

  9. Mordohai, P., Frahm, J.M., Akbarzadeh, A., Clipp, B., Engels, C., Gallup, D., Merrell, P., Salmi, C., Sinha, S., Talton, B., Wang, L., Yang, Q., Stewnius, H., Towles, H., Welch, G., Yang, R., Pollefeys, M., Nistr, D.: Real-time video-based reconstruction of urban environments. In: 3D-ARCH 2007: 3D Virtual Reconstruction and Visualization of Complex Architectures, Zurich, Switzerland, July 2007

    Google Scholar 

  10. Clipp, B., Welch, G., Frahm, J.-M., Pollefeys, M.: Structure from motion via a two-stage pipeline of extended Kalman filters. In: Proceedings of the British Machine Vision Conference 2007 (BMVC 2007), British Machine Vision Association, BMVA (2007)

    Google Scholar 

  11. Pollefeys, M., Nistr, D., Frahm, J.-M., Akbarzadeh, A., Mordohai, P., Clipp, B., Engels, C., Gallup, D., Kim, S.J., Merrell, P., Salmi, C., Sinha, S., Talton, B., Wang, L., Yang, Q., Stewnius, H., Yang, R., Welch, G., Towles, H.: Detailed real-time urban 3D reconstruction from video. Int. J. Comput. Vis. 78(2–3), 143–167 (2008)

    Article  Google Scholar 

  12. Clipp, B., Raguram, R., Frahm, J.-M., Welch, G., Pollefeys, M.: A mobile 3D city reconstruction system. In: IEEE VR workshop on Cityscapes, March 2008

    Google Scholar 

  13. Beardsley, P.A., Zisserman, A., Murray, D.W.: Sequential updating of projective and affine structure from motion. Int. J. Comput. Vis. 23(3), 235–259 (1997)

    Article  Google Scholar 

  14. Bleser, G., Becker, M., Stricker, D.: Real-time vision-based tracking and reconstruction. J. Real-Time Image Proc. 2(2–3), 161–175 (2007)

    Article  Google Scholar 

  15. Eade, E., Drummond, T.: Scalable monocular SLAM. In: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, (CVPR 2006), vol. 1, pp. 469–476. IEEE Computer Society, Washington, D.C. (2006)

    Google Scholar 

  16. Welch, G., Bishop, G.: An introduction to the Kalman filter. In: Tutorial of SIGGRAPH 2001, pp. 1–81 (2001)

    Google Scholar 

  17. Lowe, D.G.: Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vis. 60(2), 91–110 (2004)

    Article  Google Scholar 

  18. Nister, D., Stewenius, H.: Scalable recognition with a vocabulary tree. In: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), vol. 2, pp. 2161–2168. IEEE Computer Society, Washington, D.C. (2006)

    Google Scholar 

  19. Chum, O., Philbin, J., Sivic, J., Isard, M., Zisserman, A.: Total recall: automatic query expansion with a generative feature model for object retrieval. In: Proceedings of the 11th International Conference on Computer Vision, Rio de Janeiro, Brazil (2007)

    Google Scholar 

  20. Charnes, A., Frome, E.L., Yu, P.L.: The equivalence of generalized least squares and maximum likelihood estimates in the exponential family. J. Am. Stat. Assoc. 71(353), 169–171 (1976)

    Article  MATH  MathSciNet  Google Scholar 

  21. Levenberg, K.: A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 2, 164–168 (1944)

    Article  MATH  MathSciNet  Google Scholar 

  22. Fischler, M.A., Bolles, R.C.: A paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981). doi:10.1145/358669.358692

    Article  Google Scholar 

  23. Xiao, J.: SFMedu. http://vision.princeton.edu/courses/SFMedu/

  24. Tomasi, C., Kanade, T.: Shape and motion from image streams under orthography: a factorization method. Int. J. Comput. Vis. 9(2), 13–154 (1992)

    Article  Google Scholar 

  25. Morita, T., Kanade, T.: A sequential factorization method for recovering shape and motion from image streams. Pattern Anal. Mach. Intell. 19(8), 858–867 (1997)

    Article  Google Scholar 

  26. Kennedy, R., Balzano, L., Wright, S.J., Taylor, C.J.: Online algorithms for factorization-based structure from motion. Comput. Vis. Image Underst. (2016). http://dblp.uni-trier.de/rec/bib/journals/corr/KennedyBWT13

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Authors and Affiliations

  1. Department of Electrical Engeneering, Indian Institute of Technology Delhi, New Delhi, India

    M. Chebiyyam, S. Chaudhury & I. N. Kar

Authors
  1. M. Chebiyyam
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  2. S. Chaudhury
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  3. I. N. Kar
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Corresponding author

Correspondence to M. Chebiyyam .

Editor information

Editors and Affiliations

  1. Indian Institute of Information Technology, Chittoor, India

    Snehasis Mukherjee

  2. GE Global Research, Bangalore, India

    Suvadip Mukherjee

  3. Indian Statistical Institute, Kolkata, India

    Dipti Prasad Mukherjee

  4. International Institute of Information Technology, Hyderabad, India

    Jayanthi Sivaswamy

  5. Indian Institute of Technology Bombay, Mumbai, India

    Suyash Awate

  6. CEDAR, Buffalo, New York, USA

    Srirangaraj Setlur

  7. International Institute of Information Technology, Hyderabad, India

    Anoop M. Namboodiri

  8. CSIR-CEERI, Pilani, Rajasthan, India

    Santanu Chaudhury

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Chebiyyam, M., Chaudhury, S., Kar, I.N. (2017). Recursive Structure from Motion. In: Mukherjee, S., et al. Computer Vision, Graphics, and Image Processing. ICVGIP 2016. Lecture Notes in Computer Science(), vol 10481. Springer, Cham. https://doi.org/10.1007/978-3-319-68124-5_10

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  • DOI: https://doi.org/10.1007/978-3-319-68124-5_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68123-8

  • Online ISBN: 978-3-319-68124-5

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