Tracking People in Indoor Environments

  • Candy Yiu
  • Suresh Singh
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4541)


Tracking the movement of people in indoor environments is useful for a variety of applications including elderly care, study of shopper behavior in shopping centers, security etc. There have been several previous efforts at solving this problem but with limited success. Our approach uses inexpensive pressure sensors, placed in a specific manner, that allows us to identify multiple people. Given this information, our algorithm can track multiple people across the floor even in the presence of large sensor error. The algorithm we develop is evaluated for a variety of different movement patterns that include turning and path crossing. The error in correct path detection is shown to be very small even in the most complex movement scenario. We note that our algorithm does not use any a priori information such as weight, rfid tags, knowledge of number of people, etc.


Sensor Network Pressure Sensor Location Error Indoor Environment Tracking Algorithm 
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.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Liu, J., Chu, M., Liu, J., Reich, J., Zhao, F.: Distributed State Representation for Tracking Problems in Sensor Networks. In: Proc. of 3rd workshop on Information Processing in Sensor Networks (2004)Google Scholar
  2. 2.
    Mori, T., Suemasu, Y., Noguchi, H., Sato, T.: Multiple People Tracking by Integrating Distributed Floor Pressure Sensors and RFID System. In: Proceedings of IEEE International Conference on System Man and Cybernetics (2004)Google Scholar
  3. 3.
    Mechitov, K., Sundresh, S., Kwon, Y., Agha, G.: Cooperative Tracking with Binary-Detection Sensor Networks. In: Proceedings of the 1st international conference on Embedded networked sensor systems (2003)Google Scholar
  4. 4.
    Savarese, C., Rabaey, J.M., Beutel, J.: Locationing in Distributed Ad-hoc Wireless Sensor Networks. In: Proc. 2001 Int’l Conf. Acoustics, Speech, and Signal Processing (2001)Google Scholar
  5. 5.
    Kaddoura, Y., King, J., Helal, A.: Cost-Precision Tradeoffs in Unencumbered Floor-based Indoor Location Tracking. International Conference On Smart homes and health Telematic (2005)Google Scholar
  6. 6.
    Headon, R., Curwen, R.: Recognizing Movements from the Ground Reaction Force. In: Proceedings of the 2001 workshop on Perceptive user interfaces (2001)Google Scholar
  7. 7.
    Orr, R.J., Abowd, G.D.: The Smart Floor: A Mechanism for Natural User Identification and Tracking. In: Proceedings of the 2000 Conference on Human Factors in Computing Systems (2000)Google Scholar
  8. 8.
    Addlesee, M.D., Jones, A.H., Livesey, F., Samaria, F.S.: The ORL Active Floor. IEEE Personal Communication (1997)Google Scholar
  9. 9.
  10. 10.

Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Candy Yiu
    • 1
  • Suresh Singh
    • 1
  1. 1.Portland State University 

Personalised recommendations