Audio-Visual Speaker Tracking with Importance Particle Filters
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.
- URL: http://publications.idiap.ch/downloads/reports/2002/rr02-37.pdf
- Related documents: http://publications.idiap.ch/index.php/publications/showcite/gatica02d
Record created on 2006-03-10, modified on 2016-08-08