Tracking the Multi Person Wandering Visual Focus of Attention
| Type of publication: | Conference paper |
| Citation: | smith:icmi:2006 |
| 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. |
| Userfields: | ipdmembership={vision}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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