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We record, and analyze, and present to the community, KrishnaCam, a large (7.6 million frames, 70 hours) egocentric video stream along with GPS position, acceleration and body orientation data spanning nine months of the life of a computer vision graduate student. We explore and exploit the inherent redundancies in this rich visual data stream to answer simple scene understanding questions such as: How much novel visual information does the student see each day? Given a single egocentricdoi:10.1109/wacv.2016.7477717 dblp:conf/wacv/SinghFE16 fatcat:aua4mbe5cjfcrclace6qy4xi44