Advertisement

Context-Aware Agents for People Detection and Stereoscopic Analysis

  • Sara Rodríguez
  • Juan F. De Paz
  • Pablo Sánchez
  • Juan M. Corchado
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 71)

Abstract

This paper presents a multiagent system that can process stereoscopic images and detect people with a stereo camera. In the first of two phases, the system creates a model of the environment using a disparity map. It can be constructed in real time, even if there are moving objects present in the area (such as people passing by). In the second phase, the system is able to detect people by combining a series of novel techniques. A multi-agent system (MAS) is used to deal with the problem. The system is based on cooperative and distributed mechanisms and was tested under different conditions and environments.

Keywords

Multi-agent systems stereo processing people detection SAD HOG 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Canny, J.: A computational approach to edge detection. IEEE Trans. Pattern Analysis and Machine Intelligence 8(6), 679–698 (1986)CrossRefGoogle Scholar
  2. 2.
    Castanedo, F., García, J., Patricio, M.A., Molina, J.M.: Designing a Visual Sensor Network Using a Multi-agent Architecture, ASC 978-3-642-00486-5, pp. 430–439 (2009)Google Scholar
  3. 3.
    Corchado, J.M., Glez-Bedia, M., de Paz, Y., Bajo, J., de Paz, J.F.: Replanning mechanism for deliberative agents in dynamic changing environments. Computational Intelligence 24(2), 77–107 (2008)CrossRefMathSciNetGoogle Scholar
  4. 4.
    Dalal, N., Triggs, B.: Histograms of Oriented Gradients for Human Detection. In: IEEE Conference Computer Vision and Pattern Recognition, USA, pp. 886–893 (2005)Google Scholar
  5. 5.
    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
  6. 6.
    Dhond, U.R., Aggarwal, J.K.: Structure From Stereo - A Review. IEEE Trans. on Systems, Man and Cybernetics 19(6) (November/December 1989)Google Scholar
  7. 7.
    Harville, M.: Stereo person tracking with adaptive plan-view templates of height and occupancy statistics. Image and Vision Computing 2, 127–142 (2004)CrossRefGoogle Scholar
  8. 8.
    Lindeberg, T.: Feature detection with automatic scale selection. International Journal of Computer Vision 30, 77–116 (1998)Google Scholar
  9. 9.
    López-Valles, J.M., et al.: Revista Iberoamericana de Inteligencia Artificial 9(27), 35–62 (2005), ISSN: 1137-3601Google Scholar
  10. 10.
    Lowe, D.G.: Object recognition from local scale-invariant features. In: Int. Conf. on Computer Vision, vol. 2, pp. 1150–1157 (1999), doi: 10.1109/ICCCV.1999.790410Google Scholar
  11. 11.
    Pedersoli, M., Gonzàlez, J., Chakraborty, B., Villanueva, J.J.: Enhancing Real-Time Human Detection Based on Histograms of Oriented Gradients. In: Computer Recognition Systems 2. ASC. Springer, Berlin (2007)Google Scholar
  12. 12.
    Point Grey Research Inc. (2009), http://www.ptgrey.com/
  13. 13.
    Rodríguez, S., De Paz, J.F., Bajo, J., Tapia, D.I., Pérez, B.: Stereo-MAS: Multi-Agent System for Image Stereo Processing. In: Cabestany, J., Sandoval, F., Prieto, A., Corchado, J.M., et al. (eds.) IWANN 2009. LNCS (LNAI), vol. 5517, pp. 1256–1263. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  14. 14.
    Sobel, I., Feldman, G.: A 3x3 Isotropic Gradient Operator for Image Processing, presentado en la conferencia Stanford Artificial Project (1968)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Sara Rodríguez
    • 1
  • Juan F. De Paz
    • 1
  • Pablo Sánchez
    • 1
  • Juan M. Corchado
    • 1
  1. 1.Departamento Informática y AutomáticaUniversidad de SalamancaSalamancaSpain

Personalised recommendations