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Audio-Visual Particle Flow SMC-PHD Filtering for Multi-Speaker Tracking

Liu, Yang, Kiliç, Volkan, Guan, Jian and Wang, Wenwu (2019) Audio-Visual Particle Flow SMC-PHD Filtering for Multi-Speaker Tracking IEEE Transactions on Multimedia.

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Abstract

Sequential Monte Carlo probability hypothesis density (SMC-PHD) filtering is a popular method used recently for audio-visual (AV) multi-speaker tracking. However, due to the weight degeneracy problem, the posterior distribution can be represented poorly by the estimated probability, when only a few particles are present around the peak of the likelihood density function. To address this issue, we propose a new framework where particle flow (PF) is used to migrate particles smoothly from the prior to the posterior probability density. We consider both zero and non-zero diffusion particle flows (ZPF/NPF), and developed two new algorithms, AV-ZPF-SMC-PHD and AV-NPFSMC- PHD, where the speaker states from the previous frames are also considered for particle relocation. The proposed algorithms are compared systematically with several baseline tracking methods using the AV16.3, AVDIAR and CLEAR datasets, and are shown to offer improved tracking accuracy and average effective sample size (ESS).

Item Type: Article
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
NameEmailORCID
Liu, Yangyangliu@surrey.ac.uk
Kiliç, Volkan
Guan, Jian
Wang, WenwuW.Wang@surrey.ac.uk
Date : 11 August 2019
Funders : EPSRC - Engineering and Physical Sciences Research Council
Grant Title : Programme Grant S3A: Future Spatial Audio for an Immersive Listener Experience at Home
Copyright Disclaimer : © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Uncontrolled Keywords : Audio-Visual Tracking; Sequential Monte Carlo; PHD filter; Particle Flow; Optimal Proposal Distribution
Depositing User : Diane Maxfield
Date Deposited : 29 Aug 2019 14:17
Last Modified : 29 Aug 2019 14:17
URI: http://epubs.surrey.ac.uk/id/eprint/852506

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