3D convolution neural network-based person identification using gait cycles-Reference-Cited by-同舟云学术

3D convolution neural network-based person identification using gait cycles

Published:2021-08-17 Issue:4 Volume:12 Page:1045-1056
ISSN:1868-6478
Container-title:Evolving Systems
language:en
Short-container-title:Evolving Systems

Author:

Supraja P.^ORCID,Tom Rijo Jackson,Tiwari Ravi Shekhar,Vijayakumar V.,Liu Yan

Publisher

Springer Science and Business Media LLC

Subject

Control and Optimization,Computer Science Applications,Modelling and Simulation,Control and Systems Engineering

Link

https://link.springer.com/content/pdf/10.1007/s12530-021-09397-y.pdf

Reference45 articles.

1. Akman O, Alatan AA, Çiloglu T (2008) Multi-camera visual surveillance for motion detection, occlusion handling, tracking and event recognition. In: workshop on multi-camera and multi-modal sensor fusion algorithms

2. Angra S, Ahuja S (2017) Machine learning and its application. IEEE. https://doi.org/10.1109/ICBDACI.2017.8070809

3. Ariyanto G, Nixon MS (2011) Model-based 3D gait biometrics. In: 2011 international joint conference on biometrics (IJCB)

4. Blanke DJ, Hageman PA (1989) Comparison of gait of young men and elderly men. Phys Ther 69(2):144–148

5. Bobick F, Johnson AY (2001) Gait recognition using static activity-specific parameters. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit 1:423–430

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