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Action Recognition Based on Joint Trajectory Maps with Convolutional Neural Networks
[article]
2016
arXiv
pre-print
Convolutional Neural Networks (ConvNets) have recently shown promising performance in many computer vision tasks, especially image-based recognition. How to effectively apply ConvNets to sequence-based data is still an open problem. This paper proposes an effective yet simple method to represent spatio-temporal information carried in 3D skeleton sequences into three 2D images by encoding the joint trajectories and their dynamics into color distribution in the images, referred to as Joint
arXiv:1612.09401v1
fatcat:bsuh6tiwnjdt7jhrjb6k3y35vi