Human action recognition based on 3D SIFT and LDA model

Liu, Ping, Wang, Jin, She, Mary and Liu, Honghai 2011, Human action recognition based on 3D SIFT and LDA model, in RiiSS 2011 : Proceedings of the 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space, IEEE, [Paris, France], pp. 1-6.

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Title Human action recognition based on 3D SIFT and LDA model
Author(s) Liu, Ping
Wang, Jin
She, Mary
Liu, Honghai
Conference name IEEE Workshop on Robotic Intelligence in Informationally Structured Space (2011 : Paris, France)
Conference location Paris, France
Conference dates 11-15 Apr. 2011
Title of proceedings RiiSS 2011 : Proceedings of the 2011 IEEE Workshop on Robotic Intelligence in Informationally Structured Space
Editor(s) [Unknown]
Publication date 2011
Series IEEE Symposium Series on Computational Intelligence
Start page 1
End page 6
Publisher IEEE
Place of publication [Paris, France]
Keyword(s) human action recognition
3D SIFT
Latent Dirichlet Allocation
Summary How to recognize human action from videos captured by modern cameras efficiently and effectively is a challenge in real applications. Traditional methods which need professional analysts are facing a bottleneck because of their shortcomings. To cope with the disadvantage, methods based on computer vision techniques, without or with only a few human interventions, have been proposed to analyse human actions in videos automatically. This paper provides a method combining the three dimensional Scale Invariant Feature Transform (SIFT) detector and the Latent Dirichlet Allocation (LDA) model for human motion analysis. To represent videos effectively and robustly, we extract the 3D SIFT descriptor around each interest point, which is sampled densely from 3D Space-time video volumes. After obtaining the representation of each video frame, the LDA model is adopted to discover the underlying structure-the categorization of human actions in the collection of videos. Public available standard datasets are used to test our method. The concluding part discusses the research challenges and future directions.
ISBN 1424498856
9781424498857
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890201 Application Software Packages (excl. Computer Games)
HERDC Research category E2 Full written paper - non-refereed / Abstract reviewed
Copyright notice ©2011, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30042251

Document type: Conference Paper
Collection: Centre for Material and Fibre Innovation
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