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Non-zero diffusion particle flow SMC-PHD filter for audio-visual multi-speaker tracking

Liu, Yang, Hilton, Adrian, Chambers, J, Zhao, Y and Wang, Wenwu (2018) Non-zero diffusion particle flow SMC-PHD filter for audio-visual multi-speaker tracking In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2018), 15 - 20 April 2018, Calgary, Alberta, Canada.

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The sequential Monte Carlo probability hypothesis density (SMC-PHD) filter has been shown to be promising for audio-visual multi-speaker tracking. Recently, the zero diffusion particle flow (ZPF) has been used to mitigate the weight degeneracy problem in the SMC-PHD filter. However, this leads to a substantial increase in the computational cost due to the migration of particles from prior to posterior distribution with a partial differential equation. This paper proposes an alternative method based on the non-zero diffusion particle flow (NPF) to adjust the particle states by fitting the particle distribution with the posterior probability density using the nonzero diffusion. This property allows efficient computation of the migration of particles. Results from the AV16.3 dataset demonstrate that we can significantly mitigate the weight degeneracy problem with a smaller computational cost as compared with the ZPF based SMC-PHD filter.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
Chambers, J
Zhao, Y
Date : 2018
Copyright Disclaimer : © 2018 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, SMC-PHD Filter, Particle Flow
Depositing User : Melanie Hughes
Date Deposited : 14 Mar 2018 15:05
Last Modified : 16 Jan 2019 19:08

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