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MIDIAS: An Integrated 2D/3D Sensor System for Safety Applications

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 5259)

Abstract

In this article we present an integrated micro-system consisting of a high resolution gray-value camera and a range camera. We discuss a flexible calibration method, which is essential for the three-dimensional reconstruction of the scene observed by the camera system. For the calibrated micro-system we present a simple and fast data fusion technique, which assigns distance information to each image pixel of the gray-value camera. Our methods enhance the resolution of the coarse distance information provided by the range camera. We demonstrate the applicability of our micro-system by two application examples within the safety domain: Front-view pedestrian recognition and intrusion detection with automated retrieval of the intruder image.

Keywords

  • Intrusion Detection
  • Data Fusion
  • Distance Information
  • Safety Application
  • Reference Coordinate System

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Beder, C., Koch, R.: Calibration of focal length and 3d pose based on the reflectance and depth image of a planar object. In: Dynamic 3D Imaging Workshop in Conjunction with DAGM 2007 (2007)

    Google Scholar 

  2. Förstner, W.: Uncertainty and projective geometry. In: Bayro-Corrochano, E. (ed.) Handbook of Computational Geometry for Pattern Recognition, Computer Vision, Neurocomputing and Robotics. Springer, Heidelberg (2004)

    Google Scholar 

  3. Gokturk, S.B., Yalcin, H., Bamji, C.: A time-of-flight depth sensor - system description, issues and solutions. In: CVPRW 2004: Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW 2004), Washington, DC, USA, vol. 3, p. 35. IEEE Computer Society, Los Alamitos (2004)

    Google Scholar 

  4. Guibas, L., Stolfi, J.: Primitives for the manipulation of general subdivisions and the computation of voronoi diagrams. ACM Trans. Graph. 4(2), 74–123 (1985)

    CrossRef  MATH  Google Scholar 

  5. Hanning, T., Lasaruk, A., Wertheimer, R.: MDSI range camera calibration. Advanced Microsystems for Automotive Applications. Springer, Heidelberg (2008)

    CrossRef  Google Scholar 

  6. Hanning, T., Schöne, R., Graf, S.: A closed form solution for monocular re-projective 3D pose estimation of regular planar patterns. In: International Conference of Image Processing (ICIP), Atlanta, Georgia, pp. 2197–2200 (2006)

    Google Scholar 

  7. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2000)

    MATH  Google Scholar 

  8. Elkhalili, O., Schrey, O.M., Mengel, P., Petermann, M., Brockherde, W., Hosticka, B.J.: A 4 x 64 pixel CMOS image sensor for 3-d measurement applications. IEEE Journal of Solid-State Circuits 39, 1208–1212 (2004)

    CrossRef  Google Scholar 

  9. Lawson, C.L., Hanson, R.J.: Solving Least Squares Problems. Prentice-Hall, Englewood Cliffs (1974)

    MATH  Google Scholar 

  10. Lindner, M., Kolb, A.: Lateral and depth calibration of pmd-distance sensors. In: Bebis, G., Boyle, R., Parvin, B., Koracin, D., Remagnino, P., Nefian, A., Meenakshisundaram, G., Pascucci, V., Zara, J., Molineros, J., Theisel, H., Malzbender, T. (eds.) ISVC 2006. LNCS, vol. 4292, pp. 524–533. Springer, Heidelberg (2006)

    CrossRef  Google Scholar 

  11. Lindner, M., Kolb, A.: Calibration of the intensity-related distance error of the PMD TOF-camera. In: Casasent, D.P., Hall, E.L., Röning, J. (eds.) Intelligent Robots and Computer Vision XXV: Algorithms, Techniques, and Active Vision. Society of Photo-Optical Instrumentation Engineers (SPIE) Conference. Proceedings of the SPIE, vol. 6764, 67640W (2007)

    Google Scholar 

  12. Mengel, P., Listl, L., Koenig, B., Pellkofer, M., Wagner, U., Wertheimer, R.: Time-of-flight camera for pedestrian protection and collision mitigation. In: 6th European Congress and Exhibition on Intelligent Transport Systems and Services (accepted, 2007)

    Google Scholar 

  13. Moeller, T., Kraft, H., Frey, J., Albrecht, M., Lange, R.: Robust 3d measurement with pmd sensors. Technical report, PMDTec. (2005)

    Google Scholar 

  14. Oggier, T., Büttgen, B., Lustenberger, F.: Swissranger sr3000 and first experiences based on miniaturized 3d-tof cameras. In: Ingensand, K. (ed.) 1st range imaging research day, Zurich, pp. 97–108 (2005)

    Google Scholar 

  15. Preparata, F.P., Shamos, M.I.: Computational geometry: an introduction. Springer, New York (1985)

    CrossRef  MATH  Google Scholar 

  16. Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T.: Numerical Recipes in C, 2nd edn. Cambridge University Press, Cambridge (1992)

    MATH  Google Scholar 

  17. Tatschke, T., Park, S.B., Amditis, A., Polychronopoulos, A., Scheunert, U., Aycard, O.: Profusion2 - towards a modular, robust and reliable fusion architecture for automotive environment perception. In: Advanced Microsystems for Automotive Applications 2006 (AMAA), pp. 451–469. Springer, Berlin (2006)

    CrossRef  Google Scholar 

  18. Walchshäusl, L., Lindl, R., Vogel, K., Tatschke, T.: Detection of road users in fused sensor data streams for collision mitigation. In: Valldorf, J., Gessner, W. (eds.) Advanced Microsystems for Automotive Applications(AMAA), pp. 53–65. Springer, Berlin (2006)

    Google Scholar 

  19. Xu, Z., Schwarte, R., Heinol, H., Buxbaum, B., Ringbeck, T.: Smart pixel - photonic mixer device (PMD). In: International Conference on Mechatronic and Machine Vision in Practice (M2VIP), Siegen, Germany, pp. 259–264 (1998)

    Google Scholar 

  20. Xuming, L.: Experimental Investigation of Photonic Mixer Device and Development of TOF 3D Ranging Systems Based on PMD Technology. Ph.D thesis, Universität Siegen (2001)

    Google Scholar 

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Hanning, T., Lasaruk, A. (2008). MIDIAS: An Integrated 2D/3D Sensor System for Safety Applications. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_18

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  • DOI: https://doi.org/10.1007/978-3-540-88458-3_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-88457-6

  • Online ISBN: 978-3-540-88458-3

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