3D audiovisual person tracking using kalman filtering and information theory

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. © Springer-Verlag Berlin Heidelberg 2007.