Protection of gait data set for preserving its privacy in deep learning pipeline
Privacy · Gait Recognition · Deep Learning
Academic research reference · 2022
Protection of gait data set for preserving its privacy in deep learning pipeline
IET Biometrics · Wiley · IET
Privacy · Gait Recognition · Deep Learning
Publication record
- Venue
- IET Biometrics
- Publisher
- Wiley · IET
- Published
- Accepted 31 July 2022
- Research area
- Privacy · Gait Recognition · Deep Learning
Research summary
Research on protecting gait datasets within deep learning pipelines through privacy preservation, de-identification and gait anonymization.
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.
Privacy-preserving gait data
See this paper in GaitScape →Modules directly informed at capability level
Suspicious movement & anomaly detection
Product signals: Behaviour patterns · Trajectory & path
Privacy-preserving movement analytics
Campus & workplace movement safety
Product signals: Behaviour patterns · Trajectory & path · Safety event
Policy-governed watchlist matching for authorized deployments
Product signals: Gait identity
The record establishes the research principles. The implementation controls are a separate GaitAI build, configured per deployment — this work does not demonstrate them.
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