Audio-Visual Speaker Tracking with Importance Particle Filters
| Type of publication: | Conference paper |
| Citation: | gatica02d-conf |
| Booktitle: | IEEE International Conference on Image Processing (ICIP) |
| Year: | 2003 |
| Crossref: | gatica02d: |
| Abstract: | We present a probabilistic methodology for audio-visual (AV) speaker tracking, using an uncalibrated wide-angle camera and a microphone array. The algorithm fuses 2-D object shape and audio information via importance particle filters (I-PFs,',','), allowing for the asymmetrical integration of AV information in a way that efficiently exploits the complementary features of each modality. Audio localization information is used to generate an importance sampling (IS) function, which guides the random search process of a particle filter towards regions of the configuration space likely to contain the true configuration (a speaker). The measurement process integrates contour-based and audio observations, which results in reliable head tracking in realistic scenarios. We show that imperfect single modalities can be combined into an algorithm that automatically initializes and tracks a speaker, switches between multiple speakers, tolerates visual clutter, and recovers from total AV object occlusion, in the context of a multimodal meeting room. |
| Userfields: | ipdmembership={speech, vision}, |
| Keywords: | |
| Projects: |
Idiap |
| Authors: | |
| Added by: | [UNK] |
| Total mark: | 0 |
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