%Aigaion2 BibTeX export from Idiap Publications
%Tuesday 03 December 2024 06:10:12 PM

@INPROCEEDINGS{smith:icmi:2006,
         author = {Smith, Kevin C. and Ba, Sil{\`{e}}ye O. and Gatica-Perez, Daniel and Odobez, Jean-Marc},
       projects = {Idiap},
          title = {Tracking the Multi Person Wandering Visual Focus of Attention},
      booktitle = {International Conference on Multimodal Interfaces ({ICMI06})},
           year = {2006},
           note = {IDIAP-RR 05-80},
       crossref = {smith:rr05-80},
       abstract = {Estimating the {\em wandering visual focus of attention} (WVFOA) for multiple people is an important problem with many applications in human behavior understanding. One such application, addressed in this paper, monitors the attention of passers-by to outdoor advertisements. To solve the WVFOA problem, we propose a multi-person tracking approach based on a hybrid Dynamic Bayesian Network that simultaneously infers the number of people in the scene, their body and head locations, and their head pose, in a joint state-space formulation that is amenable for person interaction modeling. The model exploits both global measurements and individual observations for the VFOA. For inference in the resulting high-dimensional state-space, we propose a trans-dimensional Markov Chain Monte Carlo (MCMC) sampling scheme, which not only handles a varying number of people, but also efficiently searches the state-space by allowing person-part state updates. Our model was rigorously evaluated for tracking and its ability to recognize when people look at an outdoor advertisement using a realistic data set.},
            pdf = {https://publications.idiap.ch/attachments/papers/2006/smith-icmi-2006.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/papers/2006/smith-icmi-2006.ps.gz},
ipdmembership={vision},
}



crossreferenced publications: 
@TECHREPORT{smith:rr05-80,
         author = {Smith, Kevin C. and Ba, Sil{\`{e}}ye O. and Gatica-Perez, Daniel and Odobez, Jean-Marc},
       projects = {Idiap},
          title = {Tracking the Multi Person Wandering Visual Focus of Attention},
           type = {Idiap-RR},
         number = {Idiap-RR-80-2005},
           year = {2005},
    institution = {IDIAP},
           note = {To appear in International Conference on Multimodal Interfaces (ICMI'06)},
       abstract = {Estimating the {\em wandering visual focus of attention} (WVFOA) for multiple people is an important problem with many applications in human behavior understanding. One such application, addressed in this paper, monitors the attention of passers-by to outdoor advertisements. To solve the WVFOA problem, we propose a multi-person tracking approach based on a hybrid Dynamic Bayesian Network that simultaneously infers the number of people in the scene, their body and head locations, and their head pose, in a joint state-space formulation that is amenable for person interaction modeling. The model exploits both global measurements and individual observations for the VFOA. For inference in the resulting high-dimensional state-space, we propose a trans-dimensional Markov Chain Monte Carlo (MCMC) sampling scheme, which not only handles a varying number of people, but also efficiently searches the state-space by allowing person-part state updates. Our model was rigorously evaluated for tracking and its ability to recognize when people look at an outdoor advertisement using a realistic data set.},
            pdf = {https://publications.idiap.ch/attachments/reports/2005/smith-idiap-rr-05-80.pdf},
     postscript = {ftp://ftp.idiap.ch/pub/reports/2005/smith-idiap-rr-05-80.ps.gz},
ipdmembership={vision},
}