A Comprehensive Approach for Evaluation of Stereo Correspondence Solutions in Augmented Reality

Bahar Pourazar, Oscar Meruvia-Pastor

2015

Abstract

This paper suggests a comprehensive approach for the evaluation of stereo correspondence techniques based on the specific requirements of outdoor augmented reality systems. To this end, we present an evaluation model that integrates existing metrics of stereo correspondence algorithms with additional metrics that consider human factors that are relevant in the context of outdoor augmented reality systems. Our model provides modified metrics of stereoacuity, average outliers, disparity error, and processing time. These metrics have been modified to provide more relevant information with respect to the target application. We evaluate our model using two stereo correspondence methods: the OpenCV implementation of the semi-global block matching, also known as SGBM, which is a modified version of the semi-global matching by Hirschmuller; and our implementation of the solution by Mei et al., known as ADCensus. To test these methods, we use a sample of fifty-two image pairs selected from the Kitti stereo dataset, which depicts many situations typical of outdoor scenery. Experimental results show that our proposed model can provide a more detailed evaluation of both algorithms. Further, we discuss areas of improvement and suggest directions for future research.

References

  1. Andreas Geiger (2012). libs.net/datasets/kitti/.
  2. KITTI Vision.http://www.cv Daniel Scharstein (2012). MiddleBury Evaluation.http:// vision.middlebury.edu/stereo/eval/.
  3. Drascic, D. and Milgram, P. (1996). Perceptual issues in augmented reality. In Electronic Imaging: Science & Technology, pages 123-134. International Society for Optics and Photonics.
  4. Feiner, S., MacIntyre, B., Höllerer, T., and Webster, A. (1997). A touring machine: Prototyping 3d mobile augmented reality systems for exploring the urban environment. Personal Technologies, 1(4):208-217.
  5. Garnham, L. and Sloper, J. (2006). Effect of age on adult stereoacuity as measured by different types of stereotest. British journal of ophthalmology, 90(1):91-95.
  6. Google Inc. (2013). Google AR Glasses. http://www. google.com/glass/start/.
  7. Hertzmann, A. and Perlin, K. (2000). Painterly rendering for video and interaction. In Proceedings of the 1st International Symposium on Non-photorealistic Animation and Rendering, NPAR 7800, pages 7-12, New York, NY, USA. ACM.
  8. Hirschmuller, H. (2008). Stereo processing by semiglobal matching and mutual information. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 30(2):328-341.
  9. Howard, I. P. and Rogers, B. J. (1995). Binocular vision and stereopsis. Oxford University Press.
  10. Jerome, C. and Witmer, B. (2005). The perception and estimation of egocentric distance in real and augmented reality environments. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, volume 49, pages 2249-2252. SAGE Publications.
  11. Kruijff, E., Swan, J., and Feiner, S. (2010). Perceptual issues in augmented reality revisited. In Mixed and Augmented Reality (ISMAR), 2010 9th IEEE International Symposium on, pages 3-12. IEEE.
  12. Livingston, M. A. (2005). Evaluating human factors in augmented reality systems. Computer Graphics and Applications, IEEE, 25(6):6-9.
  13. Mei, X., Sun, X., Zhou, M., Jiao, S., Wang, H., and Zhang, X. (2011). On building an accurate stereo matching system on graphics hardware. In Computer Vision Workshops (ICCV Workshops), 2011 IEEE International Conference on, pages 467-474. IEEE.
  14. Pfautz, J. D. (2000). Depth perception in computer graphics. PhD thesis, University of Cambridge.
  15. Reading, R. (1983). Binocular vision: Foundations and applications. Butterworths.
  16. Scharstein, D. and Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1-3):7-42.
  17. Swan, J. E., Jones, A., Kolstad, E., Livingston, M. A., and Smallman, H. S. (2007). Egocentric depth judgments in optical, see-through augmented reality. Visualization and Computer Graphics, IEEE Transactions on, 13(3):429-442.
  18. Szeliski, R. (2011). Computer vision: algorithms and applications. Springer.
  19. Wann, J. P., Rushton, S., and Mon-Williams, M. (1995). Natural problems for stereoscopic depth perception in virtual environments. Vision research, 35(19):2731- 2736.
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Paper Citation


in Harvard Style

Pourazar B. and Meruvia-Pastor O. (2015). A Comprehensive Approach for Evaluation of Stereo Correspondence Solutions in Augmented Reality . In Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015) ISBN 978-989-758-091-8, pages 5-13. DOI: 10.5220/0005272500050013


in Bibtex Style

@conference{visapp15,
author={Bahar Pourazar and Oscar Meruvia-Pastor},
title={A Comprehensive Approach for Evaluation of Stereo Correspondence Solutions in Augmented Reality},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)},
year={2015},
pages={5-13},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005272500050013},
isbn={978-989-758-091-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications - Volume 3: VISAPP, (VISIGRAPP 2015)
TI - A Comprehensive Approach for Evaluation of Stereo Correspondence Solutions in Augmented Reality
SN - 978-989-758-091-8
AU - Pourazar B.
AU - Meruvia-Pastor O.
PY - 2015
SP - 5
EP - 13
DO - 10.5220/0005272500050013