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 [BibTeX] [Marc21]
A Multiple Hypothesis Gaussian Mixture Filter for Acoustic Source Localization and Tracking
Type of publication: Conference paper
Citation: Oualil_IWAENC_2012
Publication status: Accepted
Booktitle: 13th International Workshop on Acoustic Signal Enhancement
Year: 2012
Month: September
Pages: 233-236
Crossref: Oualil_Idiap-RR-09-2012:
Abstract: In this work, we address the problem of tracking an acoustic source based on measured time differences of arrival (TDOA). The classical solution to this problem consists in using a detector, which estimates the TDOA for each microphone pair, and then applying a tracking algorithm, which integrates the “measured” TDOAs in time. Such a two-stage approach presumes 1) that TDOAs can be estimated reliably; and 2) that the errors in detection behave in a well-defined fashion. The presence of noise and reverberation, however, causes larger errors in the TDOA estimates and, thereby, ultimately lowers the tracking performance. We propose to counteract this effect by considering a multiple hypothesis filter, which propagates the TDOA estimation uncertainty to the tracking stage. That is achieved by considering multiple TDOA estimates and then integrating the resulting TDOA observations in the framework of a Gaussian mixture filter. Experimental results show that the proposed filter has a significantly lower angular error than a multiple hypothesis particle filter.
Projects FP 7
Authors Oualil, Youssef
Faubel, Friedrich
Klakow, Dietrich
Editors Oualil, Youssef
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Total mark: 0
  • Oualil_IWAENC_2012.pdf