DKD–DAD: a novel framework with discriminative kinematic descriptor and deep attention-pooled descriptor for action recognition-Reference-Cited by-同舟云学术

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DKD–DAD: a novel framework with discriminative kinematic descriptor and deep attention-pooled descriptor for action recognition

Published:2019-02-08 Issue:9 Volume:32 Page:5285-5302
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Tong Ming,Li Mingyang,Bai He,Ma Lei,Zhao Mengao

Funder

Shaanxi Province key project of Research and Development Plan research project

International Cooperation Project of Shaanxi Province research project

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

http://link.springer.com/article/10.1007/s00521-019-04030-1/fulltext.html

Reference71 articles.

1. Soomro K, Zamir AR, Shah M (2012) UCF101: a dataset of 101 human actions classes from videos in the wild. arXiv:1212.0402

2. Kuehne H, Jhuang H, Garrote E, Poggio T, Serre T (2011) HMDB: a large video database for human motion recognition. In: Proceedings of IEEE international conference on computer vision (ICCV), pp 2556–2563

3. Laptev I, Marszalek M, Schmid C, Rozenfeld B (2008) Learning realistic human actions from movies. In: Proceedings of IEEE international conference on computer vision and pattern recognition (CVPR), pp 1–8

4. Laptev I (2005) On space-time interest points. Int J Comput Vis 64(2–3):107–123

5. Dollar P, Rabaud V, Cottrell G, Belongie S (2005) Behavior recognition via sparse spatio-temporal features. In: Proceedings of the 14th international conference on computer communications and networks (ICCCN), pp 65–72

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