You are not logged in.
Openly accessible

Efficient duration and hierarchical modeling for human activity recognition

Duong, Thi, Phung, Dinh, Bui, Hung and Venkatesh, Svetha 2009, Efficient duration and hierarchical modeling for human activity recognition, Artificial intelligence, vol. 173, no. 7-8, pp. 830-856, doi: 10.1016/j.artint.2008.12.005.

Attached Files
Name Description MIMEType Size Downloads
venkatesh-efficientduration-2009.pdf Published version application/pdf 2.51MB 141

Title Efficient duration and hierarchical modeling for human activity recognition
Author(s) Duong, Thi
Phung, DinhORCID iD for Phung, Dinh orcid.org/0000-0002-9977-8247
Bui, Hung
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Journal name Artificial intelligence
Volume number 173
Issue number 7-8
Start page 830
End page 856
Total pages 27
Publisher Elsevier BV
Place of publication Amsterdam, Netherlands
Publication date 2009-05
ISSN 0004-3702
1872-7921
Keyword(s) coxian
duration modeling
hidden semi-markov model
human activity recognition
smart surveillance
Notes Reproduced with the kind permission of the copyright owner.
Language eng
DOI 10.1016/j.artint.2008.12.005
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2009, Elsevier B.V. All rights reserved.
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044210

Document type: Journal Article
Collections: School of Information Technology
Open Access Collection
Connect to link resolver
 
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.

Versions
Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 47 times in TR Web of Science
Scopus Citation Count Cited 61 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 296 Abstract Views, 141 File Downloads  -  Detailed Statistics
Created: Thu, 05 Apr 2012, 15:58:00 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.