We present the first eye-tracking dataset for unconstrained ego-centric videos. The dataset captures over 6 hours of subjects performing common daily activities. These activities are manually annotated as socializing, walking, object manipulating, transiting and observing.
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Reverse Engineering Visual Intelligence for cognitiVe Enhancement (REVIVE) programme funded by the Joint Council Office (JCO) of A*STAR. Grant No: 1335h00098
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