Abstract:Joint attention refers to the shared focal points of attention for occupants in a space. In this work, we introduce a computational definition of joint attention for the automated editing of meetings in multi-camera environments from the AMI corpus. Using extracted head pose and individual headset amplitude as features, we developed three editing methods:(1) a naive audio-based method that selects the camera using only the headset input, (2) a rule-based edit that selects cameras at a fixed pacing using pose d… Show more
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