NDLI: Human action recognition using similarity degree between postures and spectral learning

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Human action recognition using similarity degree between postures and spectral learning

Content Provider	IET Digital Library
Author	Ding, Wenwen Liu, Kai Chen, Hao Tang, Fengqin
Abstract	In recent years, there has been renewed interest in developing methods for skeleton-based human action recognition. In this study, the challenging problem of the similarity degree of skeleton-based human postures is addressed. Human posture is described by screw motions between 3D rigid bodies, which can be seen as a relation matrix of 3D rigid bodies (RMRB3D). A linear subspace, a point of a Grassmannian manifold, is spanned by the orthonormal basis of matrix RMRB3D. A powerful way to compute the similarity degree between postures is researched to solve the geodesic distance between points on the Grassmannian manifold. Then representative postures are extracted through spectral clustering over representative postures. An action will be represented by a symbol sequence generated with a global linear eigenfunction constructed by spectral embedding. Finally, dynamic time warping and hidden Markov model (HMM) are used to classify these action sequences. The experimental evaluations of the proposed method on several challenging 3D action datasets show that the proposed approaches achieve promising results compared with other skeleton-based human action recognition algorithms.
Starting Page	110
Ending Page	117
Page Count	8
ISSN	17519632
Volume Number	12
e-ISSN	17519640
Issue Number	Issue 1, Feb (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-cvi/12/1
Journal	IET Computer Vision
Publisher Date	2017-08-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Action Sequences Computer Vision And Image Processing Technique Dynamic Time Warping Eigen Values And Eigen Function Feature Extraction Geodesic Distance Global Linear Eigenfunction Grassmannian Manifold Hidden Markov Model HMM Human Action Recognition Image Motion Analysis Image Recognition Image Sequence Knowledge Engineering Technique Learning in AI Linear Algebra Markov Processes Matrix Algebra Matrix RMRB3D Orthonormal Basis Numerical Analysis Pattern Clustering Relation Matrix of 3D Rigid Bodies Representative Postures Screw Motions Skeleton-based Human Action Recognition Skeleton-based Human Posture Similarity Degree Spectral Clustering Spectral Embedding Spectral Learning Symbol Sequence
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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