Gait-Based Human Recognition by Classification of Cyclostationary Processes on Nonlinear Shape Manifolds

DOI10.1198/016214507000000464zbMath1333.62017OpenAlexW2087358446MaRDI QIDQ3632573

Anuj Srivastava, David M. Kaziska

Publication date: 12 June 2009

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1198/016214507000000464

zbMATH Keywords

shape analysisbiometricsgait recognitionshape classificationstatistics on shape manifolds

Mathematics Subject Classification ID

Related Items (8)

Nonparametric estimation of means on Hilbert manifolds and extrinsic analysis of mean shapes of contours ⋮ On the definition of phase and amplitude variability in functional data analysis ⋮ Statistics of time warpings and phase variations ⋮ Analysis of spatio-temporal mobile phone data: a case study in the metropolitan area of Milan ⋮ FunCC: a new bi-clustering algorithm for functional data with misalignment ⋮ \(k\)-mean alignment for curve clustering ⋮ Joint Gait-Cadence Analysis for Human Identification Using an Elastic Shape Framework ⋮ Spherical Regression Models Using Projective Linear Transformations

This page was built for publication: Gait-Based Human Recognition by Classification of Cyclostationary Processes on Nonlinear Shape Manifolds