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3D Audiovisual Person Tracking Using Kalman Filtering and Information Theory

  • Nikos Katsarakis
  • George Souretis
  • Fotios Talantzis
  • Aristodemos Pnevmatikakis
  • Lazaros Polymenakos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4122)

Abstract

This paper proposes a system for tracking people in three dimensions, utilizing audiovisual information from multiple acoustic and video sensors. The proposed system comprises a video and an audio subsystem combined using a Kalman filter. The video subsystem combines in 3D a number of 2D trackers based on a variation of Stauffer’s adaptive background algorithm with spacio-temporal adaptation of the learning parameters and a Kalman tracker in a feedback configuration. The audio subsystem uses an information theoretic metric upon a pair of microphones to estimate the direction from which sound is arriving from. Combining measurements from a series of pairs the actual coordinate of the speaker in space is derived.

Keywords

Kalman Filter Foreground Pixel Acoustic Source Microphone Array Time Delay Estimation 
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.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Nikos Katsarakis
    • 1
  • George Souretis
    • 1
  • Fotios Talantzis
    • 1
  • Aristodemos Pnevmatikakis
    • 1
  • Lazaros Polymenakos
    • 1
  1. 1.Athens Information Technology, Autonomic and Grid Computing, P.O. Box 64, Markopoulou Ave., 19002 PeaniaGreece

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