Tracking without Background Model for Time-of-Flight Cameras

  • Luca Bianchi
  • Riccardo Gatti
  • Luca Lombardi
  • Paolo Lombardi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5414)

Abstract

Time-of-flight (TOF) cameras are relatively new sensors that provide a 3D measurement of a scene. By means of the distance signal, objects can be separated from the background on the basis of their distance from the sensor. For virtual studios applications, this feature can represent a revolution as virtual videos can be produced without a studio. When TOF cameras become available to the consumer market, everybody may come to be a virtual studio director. We study real-time fast algorithms to enable unprofessional virtual studio applications by TOF cameras. In this paper we present our approach to foreground segmentation, based on smart-seeded region growing and Kalman tracking. With respect to other published work, this method allows for working with a non-stationary camera and with multiple actors or moving objects in the foreground providing high accuracy for real-time computation.

Keywords

Time-of-flight cameras region growing tracking virtual studio 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Luca Bianchi
    • 1
  • Riccardo Gatti
    • 1
  • Luca Lombardi
    • 1
  • Paolo Lombardi
    • 1
  1. 1.Dept. of Computer Engineering and Systems ScienceUniversity of PaviaPaviaItaly

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