Advances in automatic gait recognition
Abstract
Automatic recognition by gait is subject to increasing interest and has the unique capability to recognize people at a distance when other biometrics are obscured. Its interest is reinforced by the longstanding computer vision interest in automated non-invasive analysis of human motion. Its recognition capability is supported by studies in other domains such as medicine (biomechanics), mathematics and psychology, which continue to suggest that gait is unique. Further, examples of recognition by gait can be found in literature, with early reference by Shakespeare concerning recognition by the way people walk. Current approaches confirm the early results that suggested gait could be used for identification, and now on much larger databases. This has been especially influenced by the human ID at a distance research program with its wide scenario of data and approaches. Gait has benefited from the developments in other biometrics and has led to new insight particularly in view of covariates. As such, gait is an interesting research area, with contributions not only to the field of biometrics but also to the stock of new techniques for the extraction and description of objects moving within image sequences.
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Gait recognition approaches are hard to hack compared with other biometric identification models.
“Besides, gait recognition approaches possess some advantages regarding other biometric identification models, since hacking such architectures poses a hard task [71].”
From Gait Recognition Based on Deep Learning: A Survey (2023) · cites this paper as [71]
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Gait Recognition Based on Deep Learning: A Survey
Filipi Gonçalves dos Santos, C., Oliveira, D. D. S., A. Passos, L., Gonçalves Pires, R., Felipe Silva Santos, D., Pascotti Valem, L., P. Moreira, T., Cleison S. Santana, M., Roder, M., Paulo Papa, J., et al. (2023) · ACM Computing Surveys · doi:10.1145/3490235 · Cited by 108 · see citing works
- Authors
- Nixon, M. S., & Carter, J. N.
- Affiliations
- University of Southampton (GB)
- ORCID
- Nixon, M.S.
- Venue
- Sixth IEEE International Conference on Automatic Face and Gesture Recognition, 2004. Proceedings.
- Publisher
- IEEE
- Published
- 2004-06-10
- Pages
- 139-144
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2100086166
- Cited by
- 92
- References
- 0
- Citations by year
- 2026: 1 · 2025: 2 · 2024: 2 · 2023: 4 · 2022: 6 · 2021: 5 · 2020: 2 · 2019: 3 · 2018: 2 · 2017: 1 · 2016: 5 · 2015: 4 · 2013: 2 · 2012: 5
- FWCI
- 13.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- ePrints Soton (University of Southampton) (acceptedVersion)
- 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 › Signal Processing › Biometric Identification and Security
- Keywords
- gait recognition, biometrics, human motion analysis, gait database, covariates, image sequences
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