Gait Recognition Using GEI and AFDEI
Open accessAbstract
Gait energy image (GEI) preserves the dynamic and static information of a gait sequence. The common static information includes the appearance and shape of the human body and the dynamic information includes the variation of frequency and phase. However, there is no consideration of the time that normalizes each silhouette within the GEI. As regards this problem, this paper proposed the accumulated frame difference energy image (AFDEI), which can reflect the time characteristics. The fusion of the moment invariants extracted from GEI and AFDEI was selected as the gait feature. Then, gait recognition was accomplished using the nearest neighbor classifier based on the Euclidean distance. Finally, to verify the performance, the proposed algorithm was compared with the GEI + 2D-PCA and SFDEI + HMM on the CASIA-B gait database. The experimental results have shown that the proposed algorithm performs better than GEI + 2D-PCA and SFDEI + HMM and meets the real-time requirements.
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Gait Energy Image reflects the sequence of a simple energy image cycle using weighted average, and sequences in a travel cycle are processed to align the binary silhouette.
“Concerning the most used methods to represent gait image data, Gait Energy Image reflects the sequence of a simple energy image cycle using the weighted average method. Further, the sequences in a travel cycle are processed to align the binary silhouette [42].”
From Gait Recognition Based on Deep Learning: A Survey (2023) · cites this paper as [42]
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Research works printed but not linked: 4
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- Authors
- Luo, J., Zhang, J., Zi, C., Niu, Y., Tian, H., & Xiu, C.
- Affiliations
- Tiangong University (CN)
- Corresponding author
- Zhang, Jianliang
- Venue
- International Journal of Optics
- Publisher
- Wiley
- Published
- 2015
- Volume
- 2015
- Pages
- 1-5
- ISSN
- 1687-9384 (ISSN-L)
- 1687-9392
- OpenAlex
- W1924008556
- Cited by
- 39
- References
- 5
- Citations by year
- 2026: 2 · 2025: 2 · 2024: 5 · 2023: 6 · 2022: 6 · 2021: 2 · 2020: 2 · 2019: 5 · 2018: 3 · 2017: 4 · 2016: 2
- FWCI
- 1.49
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- International Journal of Optics (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (61203302, 61403277, 14JCYBJC18900)
- Tianjin Research Program of Application Foundation and Advanced Technology (61203302, 61403277, 14JCYBJC18900)
- 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 › Image Retrieval and Classification Techniques
- Keywords
- gait recognition, gait energy image, moment invariants, feature fusion, nearest neighbor classification
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