中文版 | English
Title

Performance Evaluation of Model-Based Gait on Multi-View Very Large Population Database With Pose Sequences

Author
Publication Years
2020-10
DOI
Source Title
ISSN
2637-6407
Volume2Issue:4Pages:421-430
Keywords
URL[Source Record]
Indexed By
SUSTech Authorship
Others
EI Accession Number
20203309048626
EI Keywords
Hosiery manufacture ; Benchmarking ; Deep learning ; Gesture recognition ; Gait analysis
ESI Classification Code
Biomechanics, Bionics and Biomimetics:461.3 ; Ergonomics and Human Factors Engineering:461.4 ; Database Systems:723.3 ; Textile Products and Processing:819.5 ; Manufacturing:913.4
Data Source
IEEE
PDF urlhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9139355
Citation statistics
Cited Times [WOS]:0
Document TypeJournal Article
Identifierhttp://kc.sustech.edu.cn/handle/2SGJ60CL/347901
DepartmentDepartment of Computer Science and Engineering
Affiliation
1.College of Computer Science and Software Engineering, Shenzhen University, Shenzhen, China
2.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China
3.Institute of Scientific and Industrial Research, Osaka University, Suita, Japan
4.Department of Computer Science and Electrical Engineering, University of Missouri–Kansas City, Kansas City, MO, USA
Recommended Citation
GB/T 7714
Weizhi An,Shiqi Yu,Yasushi Makihara,et al. Performance Evaluation of Model-Based Gait on Multi-View Very Large Population Database With Pose Sequences[J]. IEEE Transactions on Biometrics, Behavior, and Identity Science,2020,2(4):421-430.
APA
Weizhi An.,Shiqi Yu.,Yasushi Makihara.,Xinhui Wu.,Chi Xu.,...&Yasushi Yagi.(2020).Performance Evaluation of Model-Based Gait on Multi-View Very Large Population Database With Pose Sequences.IEEE Transactions on Biometrics, Behavior, and Identity Science,2(4),421-430.
MLA
Weizhi An,et al."Performance Evaluation of Model-Based Gait on Multi-View Very Large Population Database With Pose Sequences".IEEE Transactions on Biometrics, Behavior, and Identity Science 2.4(2020):421-430.
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