Based on human bone joints, skeleton information has clear and simple
features and is not easily affected by appearance factors. In this paper, an
improved feature of Gist, ExGist, is proposed to describe the skeleton
information of human bone joints for human action recognition. The joint
coordinates are extracted by using OpenPose and the thermodynamic diagram,
and ExGist is used for feature extraction. The advantage of ExGist is that
it can effectively characterize the local and global features of skeleton
information while maintaining the original advantages of Gist feature.
Compared with Gist, ExGist achieves better results on different classifiers.
Additionally, compared with C3D and APTNet, our model also obtains better
results with an accuracy rate of 89.2%.
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