Advertisement

Human Detection with a Multi-sensors Stereovision System

  • Y. Benezeth
  • P. M. Jodoin
  • B. Emile
  • H. Laurent
  • C. Rosenberger
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)

Abstract

In this paper, we propose a human detection process using Far-Infrared (FIR) and daylight cameras mounted on a stereovision setup. Although daylight or FIR cameras have long been used to detect pedestrians, they nonetheless suffer from known limitations. In this paper, we present how both can collaborate inside a stereovision setup to reduce the false positive rate inherent to their individual use. Our detection method is based on two distinctive steps. First, human positions are detected in both FIR and daylight images using a cascade of boosted classifiers. Then, both results are fused based on the geometric information of the sterovision system. In this paper, we present how human positions are localized in images, and how the decisions taken by each camera are fused together. In order to gauge performances, a quantitative evaluation based on an annotated dataset is presented.

References

  1. 1.
    Gavrila, D.M.: The Visual Analysis of Human Movement: A Survey. In: Proc. of CVIU, vol. 73, pp. 82–98 (1999)Google Scholar
  2. 2.
    Wren, C.R., Azarbayejani, A., Darrell, T., Pentland, A.P.: Pfinder: Real-Time Tracking of the Human Body. IEEE Trans. PAMI 19, 780–785 (1997)Google Scholar
  3. 3.
    Dalal, N., Triggs, B., Schmid, C.: Human detection using oriented histograms of flow and appearance. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3952, pp. 428–441. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Viola, P., Jones, M.: Rapid object detection using a boosted cascade of simple features. In: IEEE Proc. CVPR, pp.511–518 (2001)Google Scholar
  5. 5.
    Bertozzi, M., Broggi, A., Lasagni, A., Del Rose, M.: Infrared Stereo Vision-based Pedestrian Detection. In: Proc. of IVS, pp. 24–29 (2005)Google Scholar
  6. 6.
    Xu, F., Liu, X., Fujimura, K.: Pedestrian Detection and Tracking With Night Vision. IEEE Trans. ITS 6, 63–71 (2005)Google Scholar
  7. 7.
    Benezeth, Y., Emile, B., Laurent, H., Rosenberger, C.: A Real Time Human Detection System Based on Far-Infrared Vision. In: Elmoataz, A., Lezoray, O., Nouboud, F., Mammass, D. (eds.) ICISP 2008 2008. LNCS, vol. 5099, pp. 76–84. Springer, Heidelberg (2008)CrossRefGoogle Scholar
  8. 8.
    Fang, Y., Yamada, K., Ninomiya, Y., Horn, B., Masaki, I.: Comparison between infrared-image-based and visible-image-based approaches for pedestrian detection. In: Proc. of IVS, pp. 505–510 (2003)Google Scholar
  9. 9.
    Bertozzi, M., Broggi, A., Felisa, M., Vezzoni, G., Del Rose, M.: Low-level Pedestrian Detection by means of Visible and Far Infra-red Tetra-vision. In: Proc. of IVS, pp. 231–236 (2006)Google Scholar
  10. 10.
    Bovik, A.: Hand Book of Image and Video Processing. Academic Press, London (2000)Google Scholar
  11. 11.
    Bouguet, J.Y., Perona, P.: Closed-form Camera Calibration in Dual-space Geometry. In: Proc. of the ECCV (1998)Google Scholar
  12. 12.
    Schapire, R.E.: The boosting approach to machine learning: An overview. In: Workshop on N.E.C. (2002)Google Scholar
  13. 13.
    Davis, J., Keck, M.: A two-stage template to person detection in thermal imagery. In: Workshop on A.C.V. (2005)Google Scholar
  14. 14.
    Davis, J., Sharma, V.: Background-subtraction using contour-based fusion of thermal and visible imagery. In: CVIU, vol. 106, pp. 162–182 (2007)Google Scholar
  15. 15.
    Hartley, R., Zisserman, A.: Multiple view geometry in computer vision. Cambridge University Press, Cambridge (2000)zbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Y. Benezeth
    • 1
  • P. M. Jodoin
    • 2
  • B. Emile
    • 3
  • H. Laurent
    • 4
  • C. Rosenberger
    • 5
  1. 1.Orange LabsCesson-SévignéFrance
  2. 2.MOIVREUniversité de SherbrookeSherbrookeCanada
  3. 3.Institut PRISMEUniversité Orléans, IUT de l’indreChâteaurouxFrance
  4. 4.ENSI de BourgesInstitut PRISMEBourges CedexFrance
  5. 5.GREYC, ENSICAENUniversité de Caen - CNRSCaenFrance

Personalised recommendations