Real Time Audio-Visual Person Tracking

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 spatio-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. Experiments show that gains are to be expected when fusion of the separate tracking systems is performed