Gatica-Perez, DanielLathoud, GuillaumeMcCowan, Iain A.Odobez, Jean-MarcMoore, Darren2006-03-102006-03-102006-03-10200310.1109/ICIP.2003.1247172https://infoscience.epfl.ch/handle/20.500.14299/228278We 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.visionspeechtext::conference output::conference proceedings::conference paper