The DOI matches its Crossref record; 45 of the 45 references it cites were found in a registry or an index.
Gait recognition: a challenging signal processing technology for biometric identification
Abstract
This article provides an overview of the basic research directions in the field of gait analysis and recognition. The recent developments in gait research indicate that gait technologies still need to mature and that limited practical applications should be expected in the immediate future. At present, there is a potential for initial deployment of gait for recognition in conjunction with other biometrics. However, future advances in gait analysis and recognition - an open, challenging research area - are expected to result in wide deployment of gait technologies not only in surveillance, but in many other applications as well. This article exposes the gait analysis and recognition problem to the signal processing community and it will stimulates the involvement of more researchers in gait research in the future.
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Cites
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Cited by
Pareek, P., & Thakkar, A. (2021) · Artificial Intelligence Review · doi:10.1007/s10462-020-09904-8 · Cited by 455
(2019) · ACM Computing Surveys · doi:10.1145/3230633 · Cited by 303
Classification of User Movement Data
Arias, P., Kelley, C., Mason, J., Bryant, K., & Roy, K. (2018) · Proceedings of the 2nd International Conference on Digital Signal Processing · doi:10.1145/3193025.3193036 · Cited by 6
Metadata
- Authors
- Boulgouris, N. V., Hatzinakos, D., & Plataniotis, K. N.
- Venue
- IEEE Signal Processing Magazine
- Published
- 2005-11
- Volume
- 22
- Issue
- 6
- Pages
- 78-90
- ISSN
- 1053-5888 (ISSN-L)
- OpenAlex
- W1977543168
- Cited by
- 362
- References
- 45
- FWCI
- 9.40
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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