A NON-LINEAR QUANTITATIVE EVALUATION APPROACH FOR DISPARITY ESTIMATION - Pareto Dominance Applied in Stereo Vision

Ivan Cabezas, Maria Trujillo

Abstract

Performance evaluation of vision algorithms is a necessary step during a research process. It may supports inter and intra technique comparisons. A fair evaluation process requires of a methodology. Disparity estimation evaluation involves multiple aspects. However, conventional approaches rely on the use of a single value as an indicator of comparative performance. In this paper a non-linear quantitative evaluation approach for disparity estimation is introduced. It is supported by Pareto dominance and Pareto optimal set concepts. The proposed approach allows different evaluation scenarios, and offers advantages over traditional evaluation approaches. The experimental validation is conducted using ground truth data. Innovative results obtained by applying the proposed approach are presented and discussed.

References

  1. Hirschm├╝ller, H. & Scharstein, D., 2009. Evaluation of Stereo Matching Costs on Images with Radiometric Differences. IEEE Transactions on Pattern Analysis and Machine Intelligence, 31(9). IEEE Computer Society, pp. 1582-1599.
  2. Kostliva, J., Cech, J. & Sara, R., 2007. Feasibility Boundary in Dense and Semi-Dense Stereo Matching. In Computer Vision and Pattern Recognition. Minneapolis, MN, USA. IEEE Computer Society, pp. 1-8.
  3. Leclerc, Y. G., Luong, Q. & Fua, P., 2000. Measuring the Self-Consistency of Stereo Algorithms. In European Conference on Computer Vision-Part I. SpringerVerlag, pp. 282-298.
  4. Neilson, D. & Yang, Y., 2008. Evaluation of Constructable Match Cost Measures for Stereo Correspondence using Cluster Ranking. In Computer Vision and Pattern Recognition. Anchorage, AK, USA. IEEE Computer Society, pp. 1-8.
  5. Scharstein, D., 2011. Middlebury Stereo Evaluation - Version 2. Retrieved January 28, 2011, from: http://vision.middlebury.edu/stereo/eval/.
  6. Scharstein, D. & Szeliski, R., 2002. A Taxonomy and Evaluation of Dense Two-Frame Stereo Correspondence Algorithms. International Journal of Computer Vision, Volume 47, pp. 7-42.
  7. Scharstein, D. & Szeliski, R., 2003. High-accuracy Stereo Depth Maps using Structured Light. In Computer Vision and Pattern Recognition. Madison, WI, USA. IEEE Computer Society, pp. I-195-I-202.
  8. Stankiewicz, O. & Wegner, K., 2008. Depth Map Estimation Software Version 3, ISO/IEC MPEG meeting M15540.
  9. Szeliski, R., 1999. Prediction Error as a Quality Metric for Motion and Stereo. In International Conference on Computer Vision, Volume 2. Kekyra, Greece. IEEE Computer Society, pp. 781-788.
  10. Szeliski, R. & Zabih, R., 2000. An Experimental Comparison of Stereo Algorithms. In Proceedings of the International Workshop on Vision Algorithms. Springer-Verlag, pp. 1-19.
  11. Van Veldhuizen, D. A. & Lamont, G. B., 1999. Multiobjective Evolutionary Algorithm Test Suites. In ACM symposium on Applied computing. San Antonio, TX, USA. ACM, pp. 351-357.
  12. Zheng-Xiang, X. & Zhi-Fang, W., 2010. Color Image Quality Assessment Based on Image Quality Parameters Perceived by Human Vision System. In International Conference on Multimedia Technology. Ningbo, China. IEEE Computer Society, pp. 1-8.
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Paper Citation


in Harvard Style

Cabezas I. and Trujillo M. (2011). A NON-LINEAR QUANTITATIVE EVALUATION APPROACH FOR DISPARITY ESTIMATION - Pareto Dominance Applied in Stereo Vision . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011) ISBN 978-989-8425-47-8, pages 704-709. DOI: 10.5220/0003374607040709


in Bibtex Style

@conference{visapp11,
author={Ivan Cabezas and Maria Trujillo},
title={A NON-LINEAR QUANTITATIVE EVALUATION APPROACH FOR DISPARITY ESTIMATION - Pareto Dominance Applied in Stereo Vision},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)},
year={2011},
pages={704-709},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003374607040709},
isbn={978-989-8425-47-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2011)
TI - A NON-LINEAR QUANTITATIVE EVALUATION APPROACH FOR DISPARITY ESTIMATION - Pareto Dominance Applied in Stereo Vision
SN - 978-989-8425-47-8
AU - Cabezas I.
AU - Trujillo M.
PY - 2011
SP - 704
EP - 709
DO - 10.5220/0003374607040709