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Person tracking using audio and depth cues

Liu, Qingju, deCampos, T, Wang, Wenwu, Jackson, Philip and Hilton, Adrian (2016) Person tracking using audio and depth cues In: International Conference on Computer Vision (ICCV) Workshop on 3D Reconstruction and Understanding with Video and Sound, 2015-12-11 - 2015-12-15, Santiago, Chile.

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In this paper, a novel probabilistic Bayesian tracking scheme is proposed and applied to bimodal measurements consisting of tracking results from the depth sensor and audio recordings collected using binaural microphones. We use random finite sets to cope with varying number of tracking targets. A measurement-driven birth process is integrated to quickly localize any emerging person. A new bimodal fusion method that prioritizes the most confident modality is employed. The approach was tested on real room recordings and experimental results show that the proposed combination of audio and depth outperforms individual modalities, particularly when there are multiple people talking simultaneously and when occlusions are frequent.

Item Type: Conference or Workshop Item (Conference Paper)
Subjects : Electronic Engineering
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
deCampos, T
Date : 15 February 2016
DOI : 10.1109/ICCVW.2015.97
Copyright Disclaimer : This paper is published with Open Access. Copyright remains with The Authors
Related URLs :
Depositing User : Symplectic Elements
Date Deposited : 06 Sep 2016 17:02
Last Modified : 20 Nov 2018 12:56

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