Egocentric Basketball Motion Planning from a Single First-Person Image

CVPR 2018 Gedas BertasiusAaron ChanJianbo Shi

We present a model that uses a single first-person image to generate an egocentric basketball motion sequence in the form of a 12D camera configuration trajectory, which encodes a player's 3D location and 3D head orientation throughout the sequence. To do this, we first introduce a future convolutional neural network (CNN) that predicts an initial sequence of 12D camera configurations, aiming to capture how real players move during a one-on-one basketball game... (read more)

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