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Hockey Action Recognition via Integrated Stacked Hourglass Network
2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
A convolutional neural network (CNN) has been designed to interpret player actions in ice hockey video. The hourglass network is employed as the base to generate player pose estimation and layers are added to this network to produce action recognition. As such, the unified architecture is referred to as action recognition hourglass network, or ARHN. ARHN has three components. The first component is the latent pose estimator, the second transforms latent features to a common frame of reference,doi:10.1109/cvprw.2017.17 dblp:conf/cvpr/FaniNCWZ17 fatcat:5slfxcc6azf2fnfiqnaek4bbwe