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Cited by 169

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

Skeleton-Based Online Action Prediction Using Scale Selection Network

Open access
Liu, Jun, Shahroudy, Amir, Wang, Gang, Duan, Ling-Yu, Kot, Alex C.·2020·IEEE Transactions on Pattern Analysis and Machine Intelligence
DOI 10.1109/tpami.2019.2898954
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Abstract

Action prediction is to recognize the class label of an ongoing activity when only a part of it is observed. In this paper, we focus on online action prediction in streaming 3D skeleton sequences. A dilated convolutional network is introduced to model the motion dynamics in temporal dimension via a sliding window over the temporal axis. Since there are significant temporal scale variations in the observed part of the ongoing action at different time steps, a novel window scale selection method is proposed to make our network focus on the performed part of the ongoing action and try to suppress the possible incoming interference from the previous actions at each step. An activation sharing scheme is also proposed to handle the overlapping computations among the adjacent time steps, which enables our framework to run more efficiently. Moreover, to enhance the performance of our framework for action prediction with the skeletal input data, a hierarchy of dilated tree convolutions are also designed to learn the multi-level structured semantic representations over the skeleton joints at each frame. Our proposed approach is evaluated on four challenging datasets. The extensive experiments demonstrate the effectiveness of our method for skeleton-based online action prediction.

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Metadata

Authors
Liu, J., Shahroudy, A., Wang, G., Duan, L.-Y., & Kot, A. C.
Venue
IEEE Transactions on Pattern Analysis and Machine Intelligence
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2020-06-01
Volume
42
Issue
6
Pages
1453-1467
ISSN
  • 0162-8828 (ISSN-L)
  • 2160-9292
  • 1939-3539
DOI
10.1109/tpami.2019.2898954
OpenAlex
W2914177721
Cited by
169
References
11
FWCI
13.30
Type
journal article
Language
en
Open access
green
Licence
Funders
  • National Research Foundation Singapore
  • Infocomm Media Development Authority, Singapore
  • National Basic Research Program of China (2015CB351806)
  • National Natural Science Foundation of China (61661146005, U1611461)

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Liu, J., Shahroudy, A., Wang, G., Duan, L.-Y., & Kot, A. C. (2020). Skeleton-Based Online Action Prediction Using Scale Selection Network. IEEE Transactions on Pattern Analysis and Machine Intelligence. https://doi.org/10.1109/tpami.2019.2898954

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