By Topic

Audio-assisted trajectory estimation in non-overlapping multi-camera networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Taj, M. ; Multimedia & Vision Group, Queen Mary Univ. of London, London ; Cavallaro, A.

We present an algorithm to improve trajectory estimation in networks of non-overlapping cameras using audio measurements. The algorithm fuses audiovisual cues in each camera's field of view and recovers trajectories in unobserved regions using microphones only. Audio source localization is performed using stereo audio and cycloptic vision (STAC) sensor by estimating the time difference of arrival (TDOA) between microphone pair and then by computing the cross correlation. Audio estimates are then smoothed using Kalman filtering. The audio-visual fusion is performed using a dynamic weighting strategy. We show that using a multi-modal sensor with combined visual (narrow) and audio (wider) field of view can enable extended target tracking in non-overlapping camera settings. In particular, the weighting scheme improves performance in the overlapping regions. The algorithm is evaluated in several multi-sensor configurations using synthetic data and compared with state of the art algorithm.

Published in:

Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on

Date of Conference:

19-24 April 2009