Please use this identifier to cite or link to this item:
Scopus Web of Science® Altmetric
Type: Conference paper
Title: Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter
Author: Hoseinnezhad, R.
Vo, B.
Vo, B.
Suter, D.
Citation: 2011 IEEE International Conference on Acoustics, Speech, and Signal Processing : Proceedings, 2011: pp.2300-2303
Publisher: IEEE
Publisher Place: USA
Issue Date: 2011
Series/Report no.: International Conference on Acoustics Speech and Signal Processing ICASSP
ISBN: 9781457705397
ISSN: 1520-6149
Conference Name: IEEE International Conference on Acoustics, Speech and Signal Processing (36th : 2011 : Prague, Czech Republic)
Statement of
Reza Hoseinnezhad, Ba-Ngu Vo, Ba-Tuong Vo, David Suter
Abstract: A new method is presented for integration of audio and visual information in multiple target tracking applications. The proposed approach uses a Bayesian filtering formulation and exploits multi-Bernoulli random finite set approximations. The work presented in this paper is the first principled Bayesian estimation approach to solve the sensor fusion problems that involve intermittent sensory data (e.g. audio data for a person who occasionally speaks.) We have examined our method with case studies from the SPEVI database. The results show nearly perfect tracking of people not only when they are silent but also when they are not visible to the camera (but speaking).
Keywords: audio-visual tracking
Bayesian filtering
random finite sets
finite set statistics
sensor fusion.
Rights: Copyright ©2011 by the Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
DOI: 10.1109/ICASSP.2011.5946942
Description (link):
Published version:
Appears in Collections:Aurora harvest 5
Computer Science publications

Files in This Item:
File Description SizeFormat 
RA_hdl_70434.pdfRestricted Access270.75 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.