Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter

Hoseinnezhad, R.; Vo, Ba-Ngu; Vo, Ba Tuong; Suter, D.

doi:10.1109/ICASSP.2011.5946942

Access Status

Fulltext not available

Authors

Hoseinnezhad, R.

Vo, Ba-Ngu

Vo, Ba Tuong

Suter, D.

Date

2011

Type

Conference Paper

Metadata

Show full item record

Citation

Hoseinnezhad, R. and Vo, B. and Vo, B.T. and Suter, D. 2011. Bayesian integration of audio and visual information for multi-target tracking using a CB-member filter, pp. 2300-2303.

Source Title

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

DOI

10.1109/ICASSP.2011.5946942

ISBN

9781457705397

School

School of Electrical Engineering and Computing

URI

http://hdl.handle.net/20.500.11937/55473

Collection

Curtin Research Publications

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). © 2011 IEEE.