Audio-visual speaker tracking with importance particle filters

We present a probabilistic method 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 ...

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Daniel Gatica-Perez, Guillaume Lathoud, Iain McCowan, Jean-Marc Odobez, Darren Moore
• Keywords: AV Object Occlusion, Fuses 2-D Object, ICIP 2003, Image Processing, Imperfect Single Modalities, Importance Particle Filters, Uncalibrated Wide-angle Camera