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Single Camera Motion Estimation: Modification of the 8-Point Method

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Intelligent Robotics and Applications (ICIRA 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8102))

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Abstract

In this paper, we modify the well-known 8-point method to make it work reliably in outdoor scenarios. It is well-known that the 8-point method is vulnerable against minor measurement noises especially if features are located far from a camera. Such situations occur often in outdoor scenarios. We offer four modifications to the 8-point method in the context of a RANSAC algorithm to make the algorithm robust against the measurement noises up to more than two pixels. The performance of the proposed method will be proved through simulation and practical results.

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References

  1. Bay, H., Tuytelaars, T., Van Gool, L.: SURF: Speeded Up Robust Features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006, Part I. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)

    Chapter  Google Scholar 

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

    Article  MathSciNet  Google Scholar 

  3. Hartley, R.: In Defense of the Eight-Point Algorithm. IEEE Trans. Pattern Anal. Mach. Intell. 19(6), 580–593 (1997)

    Article  Google Scholar 

  4. Hongdong, L., Richard, H.: Five-Point Motion Estimation Made Easy. In: 18th International Conference on Pattern Recognition, pp. 630–633 (2006)

    Google Scholar 

  5. Longuet-Higgins, H.C.: A Computer Algorithm for Reconstructing a Scene from Two Projections. Readings in Computer Vision 293, 133–135 (1981)

    Google Scholar 

  6. Nistér, D.: An Efficient Solution to the Five-Point Relative Pose Problem. IEEE Trans. Pattern Anal. Mach. Intell. 26(6), 756–777 (2004)

    Article  Google Scholar 

  7. Luong, Q., et al.: On Determining the Fundamental Matrix: Analysis of Different Methods and Experimental Results (1993)

    Google Scholar 

  8. Strasdat, H.: Scale Drift-Aware Large Scale Monocular SLAM. In: Proceedings of Robotics: Science and Systems, Zaragoza, Spain (June 2010)

    Google Scholar 

  9. Tsai, R.Y., Huang, T.S.: Uniqueness and Estimation of Three-Dimensional Motion Parameters of Rigid Objects with Curved Surfaces. IEEE Trans. Pattern Anal. Mach. Intell. 6(1), 13–27 (1984)

    Article  MathSciNet  Google Scholar 

  10. Zhao, L., et al.: Parallax Angle Parametrization for Monocular SLAM. In: IEEE International Conference on Robotics and Automation, pp. 3117–3124 (2011)

    Google Scholar 

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Mirabdollah, M.H., Mertsching, B. (2013). Single Camera Motion Estimation: Modification of the 8-Point Method. In: Lee, J., Lee, M.C., Liu, H., Ryu, JH. (eds) Intelligent Robotics and Applications. ICIRA 2013. Lecture Notes in Computer Science(), vol 8102. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40852-6_14

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  • DOI: https://doi.org/10.1007/978-3-642-40852-6_14

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-40851-9

  • Online ISBN: 978-3-642-40852-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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