We present and solve the speaker diarization problem in a novel way. We hypothesize that the gesturer is the speaker and that identifying the gesturer can be taken as identifying the active speaker. We provide evidence in support of the hy pothesis from gesture literature and audio-visual synchrony studies. We also present a vision-only diarization algorithm that relies on gestures (i.e. upper body movements). Experi ments carried out on 8.9 hours of a publicly available dataset (the AMI

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... data) show that diarization error rates as low as 15% can be achieved.