Output details
11 - Computer Science and Informatics
University of Dundee
Article title
Action categorization by structural probabilistic latent semantic analysis
Type
D - Journal article
Title of journal
Computer Vision and Image Understanding
Article number
-
Volume number
114
Issue number
8
First page of article
857
ISSN of journal
1077-3142
Year of publication
2010
URL
-
Number of additional authors
1
Additional information
<23> This paper proposed a new approach called structural pLSA (SpLSA) to model explicitly word dependencies by introducing latent variables, which is ignored by traditional pLSA. Accordingly, it developed an action categorization approach that learns action representations as the distribution of latent topics in an unsupervised way. Rigorous and comparative studies on two datasets with six existing models show that this approach achieved higher accuracy than five of them or comparative with the rest. This work is supported by INSIGHT (GR/S63687/01 ) project funded by EPSRC and MOD DSTL.
Interdisciplinary
-
Cross-referral requested
-
Research group
None
Citation count
10
Proposed double-weighted
No
Double-weighted statement
-
Reserve for a double-weighted output
No
Non-English
No
English abstract
-
