%Aigaion2 BibTeX export from Idiap Publications
%Tuesday 18 June 2024 10:12:35 AM

@INPROCEEDINGS{gatica05c-conf,
         author = {Gatica-Perez, Daniel and Lathoud, Guillaume and Odobez, Jean-Marc and McCowan, Iain A.},
       projects = {Idiap},
          title = {Multimodal Multispeaker Probabilistic Tracking in Meetings},
      booktitle = {Proc. Int. Conf. on Multimodal Interfaces (ICMI)},
           year = {2005},
       crossref = {gatica05c},
       abstract = {Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track the location and speaking activity of multiple speakers in a multisensor meeting room, equipped with a small microphone array and multiple uncalibrated cameras. Our framework is based on a mixed-state dynamic graphical model defined on a multiperson state-space, which includes the explicit definition of a proximity-based interaction model. The model integrates audio-visual (AV) data through a novel observation model. Audio observations are derived from a source localization algorithm. Visual observations are based on models of the shape and spatial structure of human heads. Approximate inference in our model, needed given its complexity, is performed with a Markov Chain Monte Carlo particle filter (MCMC-PF,',','),
 which results in high sampling efficiency. We present results -based on an objective evaluation procedure- that show that our framework (1) is capable of locating and tracking the position and speaking activity of multiple meeting participants engaged in real conversations with good accuracy; (2) can deal with cases of visual clutter and partial occlusion; and (3) significantly outperforms a traditional sampling-based approach.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr-04-66.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr-04-66.ps.gz},
ipdmembership={speech, vision},
}



crossreferenced publications: 
@TECHREPORT{gatica05c,
         author = {Gatica-Perez, Daniel and Lathoud, Guillaume and Odobez, Jean-Marc and McCowan, Iain A.},
       projects = {Idiap},
          title = {Multimodal Multispeaker Probabilistic Tracking in Meetings},
           type = {Idiap-RR},
         number = {Idiap-RR-66-2004},
           year = {2004},
    institution = {IDIAP},
        address = {Martigny, Switzerland},
           note = {in Proc. Int. Conf. on Multimodal Interfaces (ICMI,',','),
 Trento, Oct. 2005.},
       abstract = {Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track the location and speaking activity of multiple speakers in a multisensor meeting room, equipped with a small microphone array and multiple uncalibrated cameras. Our framework is based on a mixed-state dynamic graphical model defined on a multiperson state-space, which includes the explicit definition of a proximity-based interaction model. The model integrates audio-visual (AV) data through a novel observation model. Audio observations are derived from a source localization algorithm. Visual observations are based on models of the shape and spatial structure of human heads. Approximate inference in our model, needed given its complexity, is performed with a Markov Chain Monte Carlo particle filter (MCMC-PF,',','),
 which results in high sampling efficiency. We present results -based on an objective evaluation procedure- that show that our framework (1) is capable of locating and tracking the position and speaking activity of multiple meeting participants engaged in real conversations with good accuracy; (2) can deal with cases of visual clutter and partial occlusion; and (3) significantly outperforms a traditional sampling-based approach.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr-04-66.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr-04-66.ps.gz},
ipdmembership={speech, vision},
language={English},
}