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Stereo Vision Based Floor Plane Extraction and Camera Pose Estimation

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Intelligent Robotics and Applications (ICIRA 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5928))

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Abstract

In this paper, we present a unified approach for floor plane extraction and camera pose estimation. A histogram based method is performed on the reconstructed 3-D points obtained by an onboard video-rate stereo vision system to extract candidate points of the floor plane and determine the pose of vision system simultaneously. The obstacle area is easily localized given the floor plane region. In order to improve reliability and accuracy of camera pose estimation results, the Least Median of Squares (LMedS) based fitting method is applied to estimate the floor plane parameters with the extracted candidate points. The precise pose of the onboard stereo vision system is directly acquired related to the floor plane parameters. Experimental results in real indoor environments are discussed and show the good performance.

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References

  1. Sappa, A.D., Dornaika, F., Ponsa, D., Gerónimo, D., López, A.: An Efficient Approach to Onboard Stereo Vision System Pose Estimation. IEEE Transactions on Intelligent Transportation Systems 9(3), 476–490 (2008)

    Article  Google Scholar 

  2. Burschka, D., Hager, G.: Scene Classification from Dense Disparity Maps in Indoor Environments. In: International Conference on Pattern Recognition, pp. 708–712 (2002)

    Google Scholar 

  3. Okada, K., Kagami, S., Inaba, M., Inoue, H.: Plane Segment Finder: Algorithm, Implementation and Applications. In: IEEE International Conference on Robotics and Automation, pp. 2120–2125 (2001)

    Google Scholar 

  4. Sabe, K., Fukuchi, M., Gutmann, J., Ohashi, T., Kawamoto, K., Yoshigahara, T.: Obstacle Avoidance and Path Planning for Humanoid Robots using Stereo Vision. In: IEEE International Conference on Robotics and Automation, pp. 592–597 (2004)

    Google Scholar 

  5. Thrun, S., Martin, C., Liu, Y., Hähnel, D., Emery-Montemerlo, R., Chakrabarti, D., Burgard, W.: A Real-Time Expectation Maximization Algorithm for Acquiring Multiplanar Maps of Indoor Environments with Mobile Robots. IEEE Transactions on Robotics and Automation 20(3), 433–443 (2004)

    Article  Google Scholar 

  6. Triebel, R., Burgard, W., Dellaert, F.: Using Hierarchical EM to Extract Planes from 3D Range Scans. In: IEEE International Conference on Robotics and Automation, pp. 4437–4442 (2005)

    Google Scholar 

  7. Labayrade, R., Aubert, D., Tarel, J.: Real Time Obstacle Detection in Stereovision on Non Flat Road Geometry Through “V-disparity” Representation. In: IEEE Intelligent Vehicle Symposium, pp. 646–651 (2002)

    Google Scholar 

  8. Broggi, A., Caraffi, C., Fedriga, R.I., Grisleri, P.: Obstacle Detection with Stereo Vision for Off-Road Vehicle Navigation. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 65–72 (2005)

    Google Scholar 

  9. Trucco, E., Isgrò, F., Bracchi, F.: Plane Detection in Disparity Space. In: International Conference on Visual Information Engineering, pp. 73–76 (2003)

    Google Scholar 

  10. Rosselot, D., Hall, E.L.: The XH-Map Algorithm: A Method to Process Stereo Video to Produce a Real-Time Obstacle Map. In: SPIE, vol. 6006(1), pp. 1–11 (2005)

    Google Scholar 

  11. Thakoor, N., Jung, S., Gao, J.: Real-time Planar Surface Segmentation in Disparity Space. In: IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2007)

    Google Scholar 

  12. Chen, L., Jia, Y.: A Parallel Reconfigurable Architecture for Real-Time Stereo Vision. In: International Conference on Embedded Software and Systems, pp. 32–39 (2009)

    Google Scholar 

  13. Rousseeuw, P.J.: Least Median of Squares Regression. Journal of the American Statistical Association 79(388), 871–880 (1984)

    Article  MATH  MathSciNet  Google Scholar 

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© 2009 Springer-Verlag Berlin Heidelberg

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Chen, L., Wang, Z., Jia, Y. (2009). Stereo Vision Based Floor Plane Extraction and Camera Pose Estimation. In: Xie, M., Xiong, Y., Xiong, C., Liu, H., Hu, Z. (eds) Intelligent Robotics and Applications. ICIRA 2009. Lecture Notes in Computer Science(), vol 5928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-10817-4_82

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  • DOI: https://doi.org/10.1007/978-3-642-10817-4_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-10816-7

  • Online ISBN: 978-3-642-10817-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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