Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods
Gait Recognition · Biometrics · Deep Learning · Computer Vision · Security
Academic research reference · 2022
Intra-class variations with deep learning-based gait analysis: A comprehensive survey of covariates and methods
Neurocomputing · Elsevier
Gait Recognition · Biometrics · Deep Learning · Computer Vision · Security
Publication record
- Venue
- Neurocomputing
- Publisher
- Elsevier
- Published
- Vol. 505, pp. 315–338 · Available online 16 July 2022
- Research area
- Gait Recognition · Biometrics · Deep Learning · Computer Vision · Security
Research summary
A survey of intra-class variation in gait analysis, covering covariates and deep learning methods for gait recognition.
Research topics
Research keywords
Research reference
Research → capability → product
This publication informs a research foundation. Connections below describe GaitAI's documented architecture; they do not establish product accuracy, clinical validation or regulatory clearance.
Gait recognition & biometrics
See this paper in GaitScape →Modules directly informed at capability level
Post-event video investigation
Product signals: Trajectory & path · Gait identity · Behaviour patterns
Policy-governed watchlist matching for authorized deployments
Product signals: Gait identity
Shared architecture · 11 additional modules
These modules share platform capabilities. The publication does not directly address their applications.
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