%Aigaion2 BibTeX export from Idiap Publications
%Thursday 21 November 2024 12:29:59 PM

@INPROCEEDINGS{Oualil_IWAENC_2012,
         author = {Oualil, Youssef and Faubel, Friedrich and Klakow, Dietrich},
         editor = {Oualil, Youssef},
       projects = {FP 7},
          month = sep,
          title = {A Multiple Hypothesis Gaussian Mixture Filter for Acoustic Source Localization and Tracking},
      booktitle = {13th International Workshop on Acoustic Signal Enhancement},
           year = {2012},
          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.},
            pdf = {https://publications.idiap.ch/attachments/papers/2012/Oualil_IWAENC_2012.pdf}
}



crossreferenced publications: 
@TECHREPORT{Oualil_Idiap-RR-09-2012,
         author = {Oualil, Youssef and Faubel, Friedrich and Klakow, Dietrich},
       keywords = {Direction of arrival estimation, Kalman filters, microphone arrays, Monte Carlo methods},
       projects = {FP 7},
          month = {3},
          title = {A Multiple Hypothesis Gaussian Mixture Filter for Acoustic Source Localization and Tracking},
           type = {Idiap-RR},
         number = {Idiap-RR-09-2012},
           year = {2012},
    institution = {Idiap},
           note = {Submitted to IEEE SSP Workshop 2012},
       abstract = {In this work, we address the problem of tracking an acoustic source based on measured time difference of arrivals (TDOAs). 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 propagating the detection uncertainty. That is achieved by sampling from the GCCs and then integrating the resulting TDOAs 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.},
            pdf = {https://publications.idiap.ch/attachments/reports/2012/Oualil_Idiap-RR-09-2012.pdf}
}