%Aigaion2 BibTeX export from Idiap Publications
%Friday 05 December 2025 11:22:55 AM

@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},
}