PARAMETER AND CONFIGURATION ANALYSIS FOR NON-LINEAR POSE ESTIMATION WITH POINTS AND LINES

Martin Schumann, Bernhard Reinert, Stefan Mueller

2012

Abstract

In markerless model-based tracking approaches image features as points or straight lines are used to estimate the pose. We introduce an analysis of parametrizations of the pose data as well as of error measurements between 2D image features and 3D model data. Further, we give a review of critical geometrical configurations as they can appear on the input data. From these results the best parameter choice for a non-linear pose estimator is proposed that is optimal by construction to handle a combined input of feature correspondences and works on an arbitrary number and choice of feature type. It uses the knowledge of the 3D model to analyze the input data for critical geometrical configurations.

References

  1. Ansar, A. and Daniilidis, K. (2003). Linear Pose Estimation from Points or Lines. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 25, pages 578-589.
  2. Christy, S. and Horaud, R. (1999). Iterative Pose Computation from Line Correspondences. Computer Vision and Image Understanding, 73:137-144.
  3. Dornaika, F. and Garcia, C. (1999). Pose Estimation using Point and Line Correspondences. Real-Time Imaging, 5:215-230.
  4. Fischler, M. A. and Bolles, R. C. (1981). Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Communications of the ACM, 24:381-395.
  5. Gao, X.-S. and Tang, J. (2006). On the Probability of the Number of Solutions for the P4P Problem. ournal of Mathematical Imaging and Vision, 25:79-86.
  6. Haralick, B., Lee, C.-N., Ottenberg, K., and Nlle, M. (1994). Review and analysis of solutions of the three point perspective pose estimation problem. International Journal of Computer Vision, 13(3):331-356.
  7. Hu, Z. Y. and Wu, F. C. (2002). A Note on the Number of Solutions of the Noncoplanar P4P Problem. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24:550-555.
  8. Kumar, R. and Hanson, A. (1994). Robust methods for estimating pose and a sensitivity analysis. Computer Vision Graphics and Image Processing: Image Understanding, 60(3):313-342.
  9. Lepetit, V., Moreno-Noguer, F., and Fua, P. (2009). EPnP: An Accurate O(n) Solution to the PnP Problem. International Journal Of Computer Vision, 81:155-166.
  10. Lowe, D. (1991). Fitting parameterized three-dimensional models to images. In IEEE Transactions on Pattern Analysis and Machine Intelligence, volume 13(5), pages 441-450.
  11. Lu, C.-P., Hager, G., and Mjolsness, E. (2000). Fast and Globally Convergent Pose Estimation from Video Images. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(6):610-622.
  12. Wolfe, W. J., Mathis, D., Sklair, C. W., and Magee, M. (1991). The Perspective View of Three Points. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13:66-73.
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Paper Citation


in Harvard Style

Schumann M., Reinert B. and Mueller S. (2012). PARAMETER AND CONFIGURATION ANALYSIS FOR NON-LINEAR POSE ESTIMATION WITH POINTS AND LINES . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012) ISBN 978-989-8565-04-4, pages 271-276. DOI: 10.5220/0003827402710276


in Bibtex Style

@conference{visapp12,
author={Martin Schumann and Bernhard Reinert and Stefan Mueller},
title={PARAMETER AND CONFIGURATION ANALYSIS FOR NON-LINEAR POSE ESTIMATION WITH POINTS AND LINES},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)},
year={2012},
pages={271-276},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003827402710276},
isbn={978-989-8565-04-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2012)
TI - PARAMETER AND CONFIGURATION ANALYSIS FOR NON-LINEAR POSE ESTIMATION WITH POINTS AND LINES
SN - 978-989-8565-04-4
AU - Schumann M.
AU - Reinert B.
AU - Mueller S.
PY - 2012
SP - 271
EP - 276
DO - 10.5220/0003827402710276