NDLI: Discovering latent attributes for human action recognition in depth sequence

Content Provider	IET Digital Library
Author	Su, Yuting Jia, Pingping Liu, An An Yang, Zhaoxuan
Abstract	A method for human action recognition in depth sequence by discovering latent attributes is proposed. Specifically, a latent attribute model to take advantage of the partwise and bodywise action attributes and their concurrence for action modelling is presented. This model can avoid the explicit definition of a completed action attribute set by designing a hidden layer as latent attributes. Moreover, the relationship between pairwise attributes can be adaptively learned in terms of the specific graphical structure without human intervention. Extensive experiments on two popular datasets and a new dataset TJU show the superiority of the proposed method over the state-of-the-arts.
Starting Page	1436
Ending Page	1438
Page Count	3
ISSN	00135194
Volume Number	50
e-ISSN	1350911X
Issue Number	Issue 20, Sep (2014)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/el/50/20
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/el.2014.1316
Journal	Electronics Letters
Publisher Date	2014-09-18
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Action Modelling Bodywise Action Attributes Computer Vision And Image Processing Technique Depth Sequence Graphical Structure Graphics Technique Hidden Layer Design Human Action Recognition Image Recognition Image Sequence LAM Latent Attribute Discovery Latent Attribute Model Object Recognition Partwise Action Attributes Solid Modelling
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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