Motion boundary emphasised optical flow method for human action recognition-Reference-Cited by-同舟云学术

Motion boundary emphasised optical flow method for human action recognition

Published:2020-07-26 Issue:6 Volume:14 Page:378-390
ISSN:1751-9632
Container-title:IET Computer Vision
language:en
Short-container-title:IET comput. vis

Author:

Peng Cheng¹,Huang Haozhi¹,Tsoi Ah‐Chung²,Lo Sio‐Long¹,Liu Yun³,Yang Zi‐yi¹

Affiliation:

1. Faculty of Information TechnologyMacau University of Science and TechnologyMacauPeople's Republic of China

2. School of Computing and Information TechnologyUniversity of WollongongWollongongAustralia

3. Zhongshan Radio Monitoring StationGuangdong528400People's Republic of China

Funder

Fundo para o Desenvolvimento das Ciências e da Tecnologia

Publisher

Institution of Engineering and Technology (IET)

Subject

Computer Vision and Pattern Recognition,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cvi.2018.5556

Reference73 articles.

1. Cheng G. Wan Y. Saudagar A.N.et al.: ‘Advances in human action recognition: a survey’.arXiv 2015 1501.0596v1

2. Laptev I. Marszalek M. Schmid C.et al.: ‘Learning realistic human actions from movies’.IEEE Conf. on Computer Vision and Pattern Recognition 2008 (CVPR 2008) Alaska USA 2008 pp.1–8

3. Dense Trajectories and Motion Boundary Descriptors for Action Recognition

4. Lo S.L. Tsoi A.C.: ‘Motion boundary trajectory for human action recognition’.Asian Conf. on Computer Vision Singapore Singapore 2014 pp.85–98

5. Krizhevsky A. Sutskever I. Hinton G.E.: ‘Imagenet classification with deep convolutional neural networks’.Advances in Neural Information Processing Systems Lake Tahoe Nevada USA 2012 pp.1097–1105

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