Researching | Human-Body Action Recognition Based on Dense Trajectories and Video Saliency

Laser & Optoelectronics Progress, Volume. 57, Issue 24, 241003(2020)

Human-Body Action Recognition Based on Dense Trajectories and Video Saliency

Deyong Gao^1,2, Zibing Kang^1、*, Song Wang^1,2, and Yangping Wang^1,3

Author Affiliations

¹School of Electronic & Information Engineering, Lanzhou Jiaotong University, Lanzhou, Gansu 730070, China;

²Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphic & Image Processing, Lanzhou, Gansu 730070, China;

³Gansu Provincial Key Laboratory of System Dynamics and Reliability of Rail Transport Equipment, Lanzhou, Gansu 730070, China

show less

Abstract Get PDF(in Chinese)

Figures&Tables (9)

References (27)

Paper Information

Cited By

Article index updated:May. 21, 2024

Citation counts are provided from Researching.

The article is cited by 1 article(s) from Researching.

Tools

Get Citation

Copy Citation Text

Deyong Gao, Zibing Kang, Song Wang, Yangping Wang. Human-Body Action Recognition Based on Dense Trajectories and Video Saliency[J]. Laser & Optoelectronics Progress, 2020, 57(24): 241003

Download Citation

EndNote(RIS)BibTex Plain Text

Set citation alerts for article

Save article for my favorites

Paper Information

Category: Image Processing

Received: Mar. 30, 2020

Accepted: May. 29, 2020

Published Online: Dec. 2, 2020

The Author Email: Kang Zibing (914764692@qq.com)

DOI:10.3788/LOP57.241003

Topics

laser devices and laser physics

Lasers and Laser Optics

laser manufacturing

Instrumentation, Measurement and Metrology