Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Action Recognition Based on Joint Trajectory Maps with Convolutional
  Neural Networks   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 Trajectory Maps (JTM), and
adopts ConvNets to learn the discriminative features for human action
recognition. Such an image-based representation enables us to fine-tune
existing ConvNets models for the classification of skeleton sequences without
training the networks afresh. The three JTMs are generated in three orthogonal
planes and provide complimentary information to each other. The final
recognition is further improved through multiply score fusion of the three
JTMs. The proposed method was evaluated on four public benchmark datasets, the
large NTU RGB+D Dataset, MSRC-12 Kinect Gesture Dataset (MSRC-12), G3D Dataset
and UTD Multimodal Human Action Dataset (UTD-MHAD) and achieved the
state-of-the-art results.

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The categories of this paper are: eess
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The categories of this paper are: acc-phys
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The categories of this paper are: mtrl-th
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-ph
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The categories of this paper are: nucl-ex
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The categories of this paper are: chem-ph
2
The categories of this paper are: math
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The categories of this paper are: patt-sol
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
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The categories of this paper are: physics
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The categories of this paper are: bayes-an
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The categories of this paper are: supr-con
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The categories of this paper are: math-ph
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The categories of this paper are: solv-int