Raul Feitosa, Priscila Dias



Demand for security and surveillance systems is getting bigger day after day. This work proposes a method that counts people and detects suspicious attitudes via video sequences of areas with moderate people access. A typical application is the security of warehouses during the night, on weekends or at any time when people access is allowed but no load movement is admissible. Specifically it focuses on detecting when a person passing by the environment carries any object belonging to the background away or leaves any object in the background, while only people movement is allowed in the area. In addition, it estimates the number of people on scene. The method consists of performing four main tasks on video sequences: a) background and foreground separation, b) background estimative dynamic update, c) people location and counting, and d) suspicious attitudes detection. The proposed background and foreground separation and background estimative update algorithms deal with illumination fluctuation and shade effects. People location and counting explores colour information and motion coherence. A prototype implementing the proposed method was built for evaluation purpose. Experiments on simulated and real video sequences are reported showing the effectiveness of the proposed approach.


  1. Atsushi, N., Hirokazu, K., Shinsaku, H. and Seiji, I., 2002. “Tracking Multiple People Using Distributed Vision Systems”. Proceedings of the IEEE International Conference on Robotics and Automation, pages 2974- 2981.
  2. Cai, Q., Mitiche, A. and Aggarwal, J. K., 1995. “Tracking Human Motion in an Indoor Environment”. IEEE, pages 215-218.
  3. Forsyth, D.A., Ponce, J., 2003. Computer Vision - A Modern Approach, Prentice Hall.
  4. Gonzalez, R. G. and Woods, R. E., 2002. Digital Image Processing; Prentice Hall.
  5. Haritaoglu, I., Harwood, D. and Davis, L. S., 2000. “W4: Real-Time Surveillance of People and their Activities”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8): 809-830.
  6. Kettnaker, V. and Zabih, R., 1999. “Counting People from Multiple Camera”. IEEE, pages 267-271.
  7. Kumar, P., Ranganath, S. and Huang, W., 2003. “Queue based Fast Background Modeling and Fast Hysteresis Thresholding for Better Foreground Segmentation”. ICICS-PCM, Singapore, 743-747.
  8. Lu, W. and Tan, Y., 2001. “A Color Histogram Based People Tracking System”. IEEE, II, pages 137-140.
  9. Piau, N. K. and Ranganath, S., 2002. “Tracking People”. IEEE, pages 370-373.
  10. Ramanan, D. and Forsyth, D. A., 2003. “Finding and Tracking People from the Bottom Up”. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'03).
  11. Roh, H., Kang, S. and Lee, S., 2000. “Multiple People Tracking Using an Appearance Model Based on Temporal Color”. IEEE, pages 643-646.
  12. Rossi, M. and Bozzoli, A., 1994. “Tracking and Counting Moving People”. In Second IEEE International Conference on Image Processing, pages 212-216.
  13. Shapiro, L.G. and Stockman, G.C., 2001. “Computer Vision”,Prentice Hall, pp. 256-260.
  14. Shio, A and Sklansky, J., 1991. “Segmentation of People in Motion”. In IEEE Workshop on Visual Motion, pages 325-332.
  15. Soelli, P., 2003. “Morfological Image Analysis Principles and Applications”. 2nd ed. Springer Verlag, NY.
  16. Wojtaszek, D. and Laganière, R., 2002. “Tracking and Recognizing People in Color Using the Earth Mover's Distance”. IEEE, pages 91-96.
  17. Wren, C., Azarbayejani, A., Darrell, T. and Pentland, A., 1997. “Pfinder: Real-Time Tracking of the Human Body”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7): 780-785.

Paper Citation

in Harvard Style

Feitosa R. and Dias P. (2006). PEOPLE COUNTING SYSTEM . In Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP, ISBN 972-8865-40-6, pages 442-448. DOI: 10.5220/0001361504420448

in Bibtex Style

author={Raul Feitosa and Priscila Dias},
booktitle={Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,},

in EndNote Style

JO - Proceedings of the First International Conference on Computer Vision Theory and Applications - Volume 2: VISAPP,
SN - 972-8865-40-6
AU - Feitosa R.
AU - Dias P.
PY - 2006
SP - 442
EP - 448
DO - 10.5220/0001361504420448