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Mosaicking Cluttered Ground Planes Based on Stereo Vision

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 4478))

Abstract

Recent stereo cameras provide reliable 3D reconstructions. These are useful for selecting ground-plane points, register them and building mosaics of cluttered ground planes. In this paper we propose a 2D Iterated Closest Point (ICP) registration method, based on the distance transform, combined with a fine-tuning-registration step using directly the image data. Experiments with real data show that ICP is robust to 3D reconstruction differences due to motion and the fine tuning step minimizes the effect of the uncertainty in the 3D reconstructions.

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References

  1. Davison, A.: Real-time simultaneous localisation and mapping with a single camera. In: IEEE Int. Conf. on Computer Vision, vol. 2, pp. 1403–1410 (2003)

    Google Scholar 

  2. Karlsson, N., Bernardo, E.D., Ostrowski, J., Goncalves, L., Pirjanian, P., Munich, M.: The vslam algorithm for robust localization and mapping. In: Proc. IEEE Int. Conf. on Robotics and Automation, Barcelona, Spain, pp. 24–29 (2005)

    Google Scholar 

  3. Se, S., Lowe, D., Little, J.: Vision-based global localization and mapping for mobile robots. IEEE Trans. on Robotics 21(3), 364–375 (2005)

    Article  Google Scholar 

  4. Besl, P.J., McKay, N.D.: A method for registration of 3-d shapes. IEEE Trans. on Pattern Analysis and Mach. Intel. 14(2), 239–256 (1992)

    Article  Google Scholar 

  5. Fisher, R.: The iterative closest point algorithm, in cvonline: On-line compendium of computer vision (2006), http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/FISHER/ICP/cvoicp.htm

  6. Rusinkiewicz, S., Levoy, M.: Efficient variants of the icp algorithm. In: Int. Conf. 3-D Digital Imaging and Modeling, pp. 145–152 (2001)

    Google Scholar 

  7. Chetverikov, D., Svirko, D., Stepanov, D., Krsek, P.: The trimmed iterative closest point algorithm. In: Int. Conf. on Pattern Recognition, vol. 3, pp. 545–548 (2002)

    Google Scholar 

  8. Biber, P., Fleck, S., Strasser, W.: A probabilistic framework for robust and accurate matching of point clouds. In: 26th Pattern Recognition Symposium (2004)

    Google Scholar 

  9. Gavrila, D., Philomin, V.: Real-time object detection for smart vehicles. In: IEEE, Int. Conf. on Computer Vision (ICCV), pp. 87–93 (1999)

    Google Scholar 

  10. Bouguet, J.: Camera calibration toolbox for matlab (2006), http://www.vision.caltech.edu/bouguetj/calib_doc/

  11. Faugeras, O.: Three-Dimensional Computer Vision - A Geometric Viewpoint. MIT Press, Cambridge (1993)

    Google Scholar 

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

    MATH  Google Scholar 

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Joan Martí José Miguel Benedí Ana Maria Mendonça Joan Serrat

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© 2007 Springer Berlin Heidelberg

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Gaspar, J., Realpe, M., Vintimilla, B., Santos-Victor, J. (2007). Mosaicking Cluttered Ground Planes Based on Stereo Vision. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds) Pattern Recognition and Image Analysis. IbPRIA 2007. Lecture Notes in Computer Science, vol 4478. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72849-8_3

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  • DOI: https://doi.org/10.1007/978-3-540-72849-8_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-72848-1

  • Online ISBN: 978-3-540-72849-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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