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Particle flow SMC-PHD filter for audio-visual multi-speaker tracking. Proc. 13th International Conference on Latent Variable Analysis and Signal Separation(LVA/ICA 2017), Grenoble, France, February 21-23, 2017.

Liu, Yang, Wang, Wenwu, Chambers, Jonathon, Kilic, Volkan and Hilton, Adrian (2017) Particle flow SMC-PHD filter for audio-visual multi-speaker tracking. Proc. 13th International Conference on Latent Variable Analysis and Signal Separation(LVA/ICA 2017), Grenoble, France, February 21-23, 2017. In: Latent Variable Analysis and Signal Separation. LVA/ICA 2017. Lecture Notes in Computer Science, 10169 . Springer, pp. 344-353. ISBN 978-3-319-53546-3 Online ISBN: 978-3-319-53547-0

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Abstract

Sequential Monte Carlo probability hypothesis density (SMC- PHD) filtering has been recently exploited for audio-visual (AV) based tracking of multiple speakers, where audio data are used to inform the particle distribution and propagation in the visual SMC-PHD filter. However, the performance of the AV-SMC-PHD filter can be affected by the mismatch between the proposal and the posterior distribution. In this paper, we present a new method to improve the particle distribution where audio information (i.e. DOA angles derived from microphone array measurements) is used to detect new born particles and visual information (i.e. histograms) is used to modify the particles with particle flow (PF). Using particle flow has the benefit of migrating particles smoothly from the prior to the posterior distribution. We compare the proposed algorithm with the baseline AV-SMC-PHD algorithm using experiments on the AV16.3 dataset with multi-speaker sequences.

Item Type: Book Section
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Liu, Yangyangliu@surrey.ac.uk
Wang, WenwuW.Wang@surrey.ac.uk
Chambers, Jonathon
Kilic, Volkan
Hilton, AdrianA.Hilton@surrey.ac.uk
Editors :
NameEmailORCID
Tichavský, P
Babaie-Zadeh, M
Michel, O
Thirion-Moreau, N
Date : 15 February 2017
Funders : EPSRC
DOI : 10.1007/978-3-319-53547-0_33
Copyright Disclaimer : © Springer International Publishing AG, 2017. The final authenticated version is available online at: https://doi.org/10.1007/978-3-319-53547-0_33
Uncontrolled Keywords : Audio-visual tracking, PHD filter, SMC implementation, multi-speaker tracking
Related URLs :
Additional Information : Part of the Lecture Notes in Computer Science book series
Depositing User : Melanie Hughes
Date Deposited : 20 Nov 2018 12:03
Last Modified : 11 Dec 2018 11:24
URI: http://epubs.surrey.ac.uk/id/eprint/849899

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