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CLEAR
2006
Springer

An Audio-Visual Particle Filter for Speaker Tracking on the CLEAR'06 Evaluation Dataset

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An Audio-Visual Particle Filter for Speaker Tracking on the CLEAR'06 Evaluation Dataset
We present an approach for tracking a lecturer during the course of his speech. We use features from multiple cameras and microphones, and process them in a joint particle filter framework. The filter performs sampled projections of 3D location hypotheses and scores them using features from both audio and video. On the video side, the features are based on foreground segmentation, multi-view face detection and upper body detection. On the audio side, the time delays of arrival between pairs of microphones are estimated with a generalized cross correlation function. In the CLEAR'06 evaluation, the system yielded a tracking accuracy (MOTA) of 71% for video-only, 55% for audio-only and 90% for combined audio-visual tracking.
Kai Nickel, Tobias Gehrig, Hazim Kemal Ekenel, Joh
Added 20 Aug 2010
Updated 20 Aug 2010
Type Conference
Year 2006
Where CLEAR
Authors Kai Nickel, Tobias Gehrig, Hazim Kemal Ekenel, John W. McDonough, Rainer Stiefelhagen
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