People Detection and Tracking from a Top-View Position Using a Time-of-Flight Camera

  • Carsten Stahlschmidt
  • Alexandros Gavriilidis
  • Jörg Velten
  • Anton Kummert
Part of the Communications in Computer and Information Science book series (CCIS, volume 368)

Abstract

This paper outlines a method for the detection and tracking of people in depth images, acquired with a low-resolution Time-of-Flight (ToF) camera. This depth sensor is placed perpendicular to the ground in order to provide distance information from a top-view position.

With usage of intrinsic and extrinsic camera parameters a ground plane is estimated and compared to the measured distances of the ToF sensor in every pixel. Differences to the expected ground plane define foreground information, which is used as regions of interest (ROIs). These regions are analyzed to distinguish persons from other objects by using a matched filter on the height-segmented depth measurements of each ROI. The proposed method separates crowds into individuals and facilitates a multi-object tracking system based on a Kalman filter.

Experiments have proven the applicability of the system for different crowding scenarios but also revealed inaccuracies of the detection of people in special cases.

Keywords

people detection top-view people tracking time-of-flight matched filter 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Bar-Shalom, J., Rong Li, X., Kirubarajan, T.: Estimation with Applications to Tracking and Navigation. John Wiley & Sons (2001)Google Scholar
  2. 2.
    Bevilacqua, A., Di Stefano, L., Azzari, P.: People tracking using a Time-of-Flight depth sensor. In: IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance (2006)Google Scholar
  3. 3.
    Beymer, D., Konolige, K.: Tracking People from a Mobile Platform. In: Siciliano, B., Dario, P. (eds.) Experimental Robotics VIII. STAR, vol. 5, pp. 234–244. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  4. 4.
    Foix, S., Alenyá, G., Torras, C.: Lock-in Time-of-Flight (ToF) Cameras: A Survey. IEEE Sensors Journal 11(9), 1917–1926 (2011)CrossRefGoogle Scholar
  5. 5.
    Gavriilidis, A., Schwerdtfeger, T., Velten, J., Schauland, S., Hohmann, L., Haselhoff, A., Boschen, F., Kummert, A.: Multisensor data fusion for advanced driver assistance systems - the Active Safety Car project. In: International Workshop on Multidimensional Systems (nDs), vol. 7, pp. 1–5 (2011)Google Scholar
  6. 6.
    Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn. Prentice Hall International, Boston (2001)Google Scholar
  7. 7.
    Hansard, M., Lee, S., Choi, O., Horaud, R.P.: Time of Flight Cameras: Principles, Methods, and Applications. Springer Briefs in Computer Science. Springer (2012)Google Scholar
  8. 8.
    Harville, M.: Stereo person tracking with short and long term plan-view appearance models of shape and color. In: Proceedings of International Conference on Advanced Video and Signal based Surveillance (AVSS), vol. 1, pp. 511–517. Santa Fe (2005)Google Scholar
  9. 9.
    Harville, M., Li, D.: Fast, Integrated Person Tracking and Activity Recognition with Plan-View Templates from a Single Stereo Camera. In: IEEE Conference on Computer Vision and Pattern Recognition, Washington (2004)Google Scholar
  10. 10.
    Helbing, D., Mukerji, P.: Crowd Disasters as Systemic Failures: Analysis of the Love Parade Disaster. Tech. rep., ETH Risk Center, Zürich (2011)Google Scholar
  11. 11.
    Mallat, S.: A Wavelet Tour of Signal Processing. Academic Press (1998)Google Scholar
  12. 12.
    PMD Technologies, PMD vision CamCube 3.0 Specsheet - High resolution 3D video camera. Tech. rep., PMD Technologies GmbH (2010)Google Scholar
  13. 13.
    Reynolds, M., Dobos, J., Peel, L., Weyrich, T., Brostow, G.: Capturing Time-of-Flight Data with Confidence. In: Proc. of IEEE Conference on Computer Vision and Pattern Recognition, CVPR (2011)Google Scholar
  14. 14.
    Ringbeck, T.: A 3D Time of Flight Camera for Object Detection. In: Optical 3-D Measurement Techniques (2007)Google Scholar
  15. 15.
    Soille, P.: Morphological Image Analysis: Principles and Applications. Springer (1999)Google Scholar
  16. 16.
    Still, G.K.: Duisburg - July 24, 2010, Love Parade Incident, Expert Report. Tech. rep., Bucks New University (2011)Google Scholar
  17. 17.
    Tanner, R., Studer, M., Zanoli, A., Hartmann, A.: People Detection and Tracking with TOF Sensor. In: IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance (2008)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Carsten Stahlschmidt
    • 1
  • Alexandros Gavriilidis
    • 1
  • Jörg Velten
    • 1
  • Anton Kummert
    • 1
  1. 1.Faculty of Electrical Engineering and Media TechnologiesUniversity of WuppertalWuppertalGermany

Personalised recommendations