Mean-Shift and Sparse Sampling Based SMC-PHD Filtering for Audio Informed Visual Speaker Tracking


Introduction

This software package is a Matlab implementation of the several PHD filtering algorithms for multi-speaker audio-visual tracking.

The folder "SMAV" contains the following three sub-folders:-

Core_files: contains the implementation of the V_SMC_PHD, AV_SMC_PHD, AVMS_SMC_PHD, and sparse_AVMS_SMC_PHD filtering algorithms for audio-visual multi-speaker tracking.

Sample_test: contains examples on how to use these algorithms.

Test_files: containts the comprehensive tests performed for generating the results in the paper referenced below.

Readme: a brief description about the code.

The pdf file of the paper is also included for detailed description about the algorithms.

More details can be found in the following paper:

  • V. Kilic, M. Barnard, W. Wang, A. Hilton and J. Kittler, "Mean-Shift and Sparse Sampling Based SMC-PHD Filtering for Audio Informed Visual Speaker Tracking", IEEE Transactions on Multimedia, vol. 18, no. 10, October 2016. [PDF]

    Download

    The Matlab software package can be downloaded from here (63.7Mbytes).

    The codes & data have also been deposited to http://dx.doi.org/10.15126/surreydata.00811616.

    Written by Volkan Kilic, moderated by Wenwu Wang, version 1.0

    If you have any questions or comments regarding this package, or if you want to report any bugs or unexpected error messages, please send an e-mail to volkan.kilic@ikc.edu.tr or w.wang@surrey.ac.uk

    Copyright 2016 V. Kilic, M. Barnard, W. Wang, A. Hilton and J. Kittler

    This software is a free software distributed under the terms of the GNU Public License version 3 (http://www.gnu.org/licenses/gpl.txt). You can redistribute it and/or modify it under the terms of this licence, for personal and non-commercial use and research purpose.

    References

  • V. Kilic, M. Barnard, W. Wang, A. Hilton and J. Kittler, "Mean-Shift and Sparse Sampling Based SMC-PHD Filtering for Audio Informed Visual Speaker Tracking", IEEE Transactions on Multimedia, vol. 18, no. 10, October 2016. [PDF]


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    Last updated on 05 April 2017
    First Created on 05 April 2017