Skip to main content

Efficient Video Mosaicking by Multiple Loop Closing

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6952))

Abstract

The rapid generation of aerial mosaics is an important task for change detection, e.g. in the context of disaster management or surveillance. Unmanned aerial vehicles equipped with a single camera offer the possibility to solve this task with moderate efforts. Unfortunately, the accumulation of tracking errors leads to a drift in the alignment of images which has to be compensated by loop closing for instance. We propose a novel approach for constructing large, consistent and undistorted mosaics by aligning video images of planar scenes. The approach allows the simultaneous closing of multiple loops possibly resulting from the camera path in a batch process. The choice of the adjustment model leads to statistical rigorous solutions while the used minimal representations for the involved homographies and the exploitation of the natural image order enable very efficient computations. The approach will be empirically evaluated with the help of synthetic data and its feasibility will be demonstrated with real data sets.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Begelfor, E., Werman, M.: How to put Probabilities on Homographies. IEEE Trans. on Pattern Recognition and Machine Intelligence 27, 1666–1670 (2005)

    Article  Google Scholar 

  2. Caballero, F., Merino, L., Ferruz, J., Ollero, A.: Homography Based Kalman Filter for Mosaic Building. Applications to UAV Position Estimation. In: IEEE International Conf. on Robotics and Automation, pp. 2004–2009 (2007)

    Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  4. Förstner, W.: Minimal Representations for Uncertainty and Estimation in Projective Spaces. In: Proc. of Asian Conf. on Computer Vision (2010)

    Google Scholar 

  5. Förstner, W., Gülch, E.: A Fast Operator for Detection and Precise Location of Distinct Points, Corners and Centres of Circular Features. In: ISPRS Intercommission Workshop, Interlaken (1987)

    Google Scholar 

  6. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  7. Koch, K.R.: Parameter Estimation and Hypothesis Testing in Linear Models, 2nd edn. Springer, Berlin (1999)

    Book  MATH  Google Scholar 

  8. Lowe, D.: Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision 60(2), 91–110 (2004)

    Article  Google Scholar 

  9. Lucas, B.T., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proc. of Image Understanding Workshop, pp. 130–212 (1981)

    Google Scholar 

  10. McGlone, J.C., Mikhail, E.M., Bethel, J. (eds.): Manual of Photogrammetry, 5th edn. American Society of Photogrammetry and Remote Sensing (2004)

    Google Scholar 

  11. Szeliski, R.: Image alignment and stitching: A tutorial. Foundations and Trends in Computer Graphics and Computer Vision 2(1), 1–104 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  12. Turkbeyler, E., Harris, C.: Mapping of Movement to Aerial Mosaic with Geo-Location Information. In: Optro 2010 (2010)

    Google Scholar 

  13. Unnikrishnan, R., Kelly, A.: A Constrained Optimization Approach to Globally Consistent Mapping. In: 2002 IEEE/RSJ Int’l Conf. on Intelligent Robots and Systems (IROS 2002), vol. 1, pp. 564–569 (2002a)

    Google Scholar 

  14. Unnikrishnan, R., Kelly, A.: Mosaicing Large Cyclic Environments for Visual Navigation in Autonomous Vehicles. In: IEEE International Conf. on Robotics and Automation (ICRA 2002), vol. 4, pp. 4299–4306 (2002b)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Meidow, J. (2011). Efficient Video Mosaicking by Multiple Loop Closing. In: Stilla, U., Rottensteiner, F., Mayer, H., Jutzi, B., Butenuth, M. (eds) Photogrammetric Image Analysis. PIA 2011. Lecture Notes in Computer Science, vol 6952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24393-6_1

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-24393-6_1

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24392-9

  • Online ISBN: 978-3-642-24393-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics