NDLI: Action recognition based on principal geodesic analysis

Content Provider	IEEE Xplore Digital Library
Author	Xiping Fu McCane, B. Albert, M. Mills, S.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci., Univ. of Otago, Dunedin, New Zealand (Xiping Fu; McCane, B.; Albert, M.; Mills, S.)
Abstract	In this paper, we consider the action recognition problem based on geometrical structure. Our method uses a low dimensional structure on the Grassmannian manifold to represent video sequences, by utilizing the linear structure of the tangent space. This approach can be divided into a training (off-line computing) stage and testing (on-line computing) stage, and makes the recognition algorithm scalable to large data sets. We test the proposed method on several benchmark data sets. The result shows that the new approach takes less computation compared to previous work based on the same geometrical assumption, and has similar or even higher recognition accuracy.
Sponsorship	IEEE New Zealand Central Sect.
Starting Page	259
Ending Page	264
File Size	357953
Page Count	6
File Format	PDF
ISSN	21512191
e-ISBN	9781479908837
DOI	10.1109/IVCNZ.2013.6727026
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-11-27
Publisher Place	New Zealand
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Manifolds Training Tensile stress Three-dimensional displays Accuracy product Space Video sequences action recognition video sequence principal geodesic analysis nonlinear manifold Testing
Content Type	Text
Resource Type	Article

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