Automatic Geometric Projector Calibration - Application to a 3D Real-time Visual Feedback

Radhwan Ben Madhkour, Matei Mancas, Bernard Gosselin

Abstract

In this paper, we present a fully automatic method for the geometric calibration of a video projector. The approach is based on the Heikkila’s camera calibration algorithm. It combines Gray coded structured light patterns projection and a RGBD camera. Any projection surface can be used. Intrinsic and extrinsic parameters are computed without a scale factor uncertainty and any prior knowledge about the projector and the projection surface. While the structured light provides pixel to pixel correspondences between the projector and the camera, the depth map provides the 3D coordinates of the projected points. Couples of pixel coordinates and their corresponding 3D coordinates are established and used as input for the Heikkila’s algorithm. The projector calibration is used as a basis to augment the scene with information from the RGBD camera in real-time.

References

  1. Ashdown, M. and Sato, Y. (2005). Steerable projector calibration. In Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops (Procams 2005). IEEE Computer Society.
  2. Audet, S. and Cooperstock, J. R. (2007). Shadow removal in front projection environments using object tracking. In Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'07) - Workshops (Procams 2007). IEEE Computer Society.
  3. Audet, S. and Okutomi, M. (2009). A user-friendly method to geometrically calibrate projector-camera systems. Computer Vision and Pattern Recognition Workshop, 0:47-54.
  4. Bouguet, J.-Y. (2010). Camera calibration toolbox for matlab.
  5. Bradski, G. and Kaehler, A. (2008). Learning OpenCV: Computer Vision with the OpenCV Library. O'Reilly.
  6. Drareni, J., Roy, S., and Sturm, P. (2009). Geometric video projector auto-calibration. In Proceedings of the 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'09) - Workshops (Procams 2009). IEEE Computer Society.
  7. Forsyth, D. and Ponce, J. (2002). Computer vision: a modern approach. Prentice Hall Professional Technical Reference.
  8. Griesser, A. and Van Gool, L. (2006). Automatic interactive calibration of multi-projector-camera systems. In Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'06) - Workshops (Procams 2006). IEEE Computer Society.
  9. Harrison, C., Benko, H., and Wilson, A. D. (2011). Omnitouch: wearable multitouch interaction everywhere. In Proceedings of the 24th annual ACM symposium on User interface software and technology (UIST'11), pages 441-450. ACM.
  10. Hartley, R. and Zisserman, A. (2004). Multiple View Geometry in Computer Vision. Cambridge University Press.
  11. Heikkila, J. (2000). Geometric camera calibration using circular control points. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10):1066- 1077.
  12. Kalal, Z., Matas, J., and Mikolajczyk, K. (2010). P-N Learning: Bootstrapping Binary Classifiers by Structural Constraints. Conference on Computer Vision and Pattern Recognition.
  13. Kimura, M., Mochimaru, M., and Kanade, T. (2007). Projector calibration using arbitrary planes and calibrated camera. In Proceedings of the 2007 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'07), pages 1-2. IEEE Computer Society.
  14. Lanman, D. and Taubin, G. (2009). Build your own 3d scanner: 3d photograhy for beginners. In SIGGRAPH 7809: ACM SIGGRAPH 2009 courses, pages 1-87, New York, NY, USA. ACM.
  15. Li, Z., Shi, Y., Wang, C., and Wang, Y. (2008). Accurate calibration method for a structured light system. Optical Engineering, 47(5):053604.
  16. Opengl, Shreiner, D., Woo, M., Neider, J., and Davis, T. (2007). OpenGL(R) Programming Guide : The Official Guide to Learning OpenGL(R), Version 2.1 (6th Edition). Addison-Wesley Professional.
  17. OpenNI (2010). Openni user guide. Last viewed 19-01- 2011 11:32.
  18. Raij, A. and Pollefeys, M. (2004). Auto-calibration of multi-projector display walls. In Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04), pages 14-17. IEEE Computer Society.
  19. Salvi, J., Pags, J., and Batlle, J. (2004). Pattern codification strategies in structured light systems. PATTERN RECOGNITION, 37(4):827-849.
  20. Sun, W. and Cooperstock, R. (2006). An empirical evaluation of factors influencing camera calibration accuracy using three publicly available techniques. Mach. Vision Appl., 17(1):51-67.
  21. Tardif, J. P., Roy, S., and Trudeau, M. (2003). Multiprojectors for arbitrary surfaces without explicit calibration nor reconstruction. In Proceedings of the Fourth International Conference on 3-D Digital Imaging and Modeling, 2003. (3DIM 2003), pages 217- 224.
  22. Yamazaki, S., Mochimaru, M., and Kanade, T. (2011). Simultaneous self-calibration of a projector and a camera using structured light. In Proceedings of the 2011 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'11) - Workshops (Procams 2011), pages 67-74. IEEE Computer Society.
  23. Zhang, Z. (2000). A flexible new technique for camera calibration. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(11):1330-1334.
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Paper Citation


in Harvard Style

Ben Madhkour R., Mancas M. and Gosselin B. (2013). Automatic Geometric Projector Calibration - Application to a 3D Real-time Visual Feedback . In Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013) ISBN 978-989-8565-48-8, pages 420-424. DOI: 10.5220/0004304604200424


in Bibtex Style

@conference{visapp13,
author={Radhwan Ben Madhkour and Matei Mancas and Bernard Gosselin},
title={Automatic Geometric Projector Calibration - Application to a 3D Real-time Visual Feedback},
booktitle={Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)},
year={2013},
pages={420-424},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004304604200424},
isbn={978-989-8565-48-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, (VISIGRAPP 2013)
TI - Automatic Geometric Projector Calibration - Application to a 3D Real-time Visual Feedback
SN - 978-989-8565-48-8
AU - Ben Madhkour R.
AU - Mancas M.
AU - Gosselin B.
PY - 2013
SP - 420
EP - 424
DO - 10.5220/0004304604200424