%Aigaion2 BibTeX export from Idiap Publications
%Thursday 21 November 2024 12:36:35 PM

@INPROCEEDINGS{gatica05b-conf,
         author = {Gatica-Perez, Daniel and Odobez, Jean-Marc and Ba, Sil{\`{e}}ye O. and Smith, Kevin C. and Lathoud, Guillaume},
       projects = {Idiap},
          title = {Tracking People in Meetings with Particles},
      booktitle = {Proc. Int. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS,',','),
 invited paper},
           year = {2005},
       crossref = {gatica05b},
       abstract = {Automatic meeting analysis is an emerging research field. In this paper, we present stochastic algorithms for tracking people in multi-sensor meeting rooms, for a number of relevant tasks, including tracking multiple people, tracking head pose towards analysis of visual focus-of-attention, and tracking speaker activity using audio-visual information. A Bayesian framework based on Sequential Monte Carlo methods is used in all cases. We discuss the advantages and limitations of our approach, illustrate it with results, and highlight a number of open issues.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr-04-71.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr-04-71.ps.gz},
ipdmembership={speech, vision},
}



crossreferenced publications: 
@TECHREPORT{gatica05b,
         author = {Gatica-Perez, Daniel and Odobez, Jean-Marc and Ba, Sil{\`{e}}ye O. and Smith, Kevin C. and Lathoud, Guillaume},
       projects = {Idiap},
          title = {Tracking People in Meetings with Particles},
           type = {Idiap-RR},
         number = {Idiap-RR-71-2004},
           year = {2004},
    institution = {IDIAP},
        address = {Martigny, Switzerland},
           note = {in Proc. Int. Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS,',','),
 invited paper, Montreux, Apr. 2005.},
       abstract = {Automatic meeting analysis is an emerging research field. In this paper, we present stochastic algorithms for tracking people in multi-sensor meeting rooms, for a number of relevant tasks, including tracking multiple people, tracking head pose towards analysis of visual focus-of-attention, and tracking speaker activity using audio-visual information. A Bayesian framework based on Sequential Monte Carlo methods is used in all cases. We discuss the advantages and limitations of our approach, illustrate it with results, and highlight a number of open issues.},
            pdf = {https://publications.idiap.ch/attachments/reports/2004/rr-04-71.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2004/rr-04-71.ps.gz},
ipdmembership={speech, vision},
language={English},
}