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Presented at: European Conference on Computer Vision Workshop on Multi-camera and Multi-modal Sensor Fusion Publication date: 2008

We propose a fully automated, unsupervised, and non-int\-rusive method of identifying the current speaker audio-vis\-ually in a group conversation. This is achieved without specialized hardware, user interaction, or prior assignment of microphones to participants. Speakers are identified acoustically using a novel on-line speaker diarization approach. The output is then used to find the corresponding person in a four-camera video stream by approximating individual activity with computationally efficient features. We present results showing the robustness of the association on over 4.5 hours of non-scripted audio-visual meeting data.

Reference LIDIAP-CONF-2008-031

Autor: Hung, Hayley; Friedland, Gerald


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