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Cited by 392Gait Recognition and AnalysisHuman Pose and Action RecognitionVideo Surveillance and Tracking Methods

Gait Recognition Using a View Transformation Model in the Frequency Domain

Makihara, Yasushi, Sagawa, Ryusuke, Mukaigawa, Yasuhiro, Echigo, Tomio, Yagi, Yasushi·2006·Lecture Notes in Computer Science
DOI 10.1007/11744078_12
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  • Cross-view-based gait recognition is a popular approach for different visual angles, requires multiple fully controlled cameras and cooperative environments, and visually normalizes gait characteristics before combination.

    “Similarly, cross-view-based gait recognition is a popular approach used to deal with different visual angles. The input type requires multiple fully controlled cameras and cooperative environments, thus being restrained to real scenarios. Moreover, it visually normalizes gait characteristics before performing any combination, which allows the model to learn the relationships among visual movements”

    From Gait Recognition Based on Deep Learning: A Survey (2023) · cites this paper as [123]

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References 28 · Cited by 392

Authors
Makihara, Y., Sagawa, R., Mukaigawa, Y., Echigo, T., & Yagi, Y.
Affiliations
The Institute of Scientific and Industrial Research, The University of Osaka (JP)
ORCID
Venue
Lecture Notes in Computer Science
Publisher
Springer Berlin Heidelberg
Published
2006
Pages
151-163
ISSN
  • 0302-9743 (ISSN-L)
  • 1611-3349
DOI
10.1007/11744078_12
OpenAlex
W1561782558
Cited by
392
References
28
Citations by year
2026: 4 · 2025: 4 · 2024: 14 · 2023: 15 · 2022: 19 · 2021: 30 · 2020: 40 · 2019: 43 · 2018: 32 · 2017: 41 · 2016: 27 · 2015: 20 · 2014: 26 · 2013: 26 · 2012: 17
FWCI
8.08
Type
conference paper
Language
en
Open access
closed
Licence
www.springer.com/tdm (tdm)
Locations
Lecture notes in computer science (publishedVersion)
Topics
  • Physical Sciences › Engineering › Biomedical Engineering › Gait Recognition and Analysis
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Human Pose and Action Recognition
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Surveillance and Tracking Methods
Keywords
gait recognition, frequency-domain features, Fourier analysis, personal identification

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