Linked Life Data

19150758

Source:http://linkedlifedata.com/resource/pubmed/id/19150758

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2009-1-19
pubmed:abstractText
Computer understanding of human actions and interactions is one of the key research issues in human computing. In this regard, context plays an essential role in semantic understanding of human behavioral and social signals from sensor data. This paper put forward an event-based dynamic context model to address the problems of context awareness in the analysis of group interaction scenarios. Event-driven multilevel dynamic Bayesian network is correspondingly proposed to detect multilevel events, which underlies the context awareness mechanism. Online analysis can be achieved, which is superior over previous works. Experiments in our smart meeting room demonstrate the effectiveness of our approach.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:status
PubMed-not-MEDLINE
pubmed:month
Feb
pubmed:issn
1941-0492
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
39
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
34-42
pubmed:year
2009
pubmed:articleTitle
Group interaction analysis in dynamic context.
pubmed:affiliation
Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, 100084 Beijing, China. daip02@mails.tsinghua.edu.cn
pubmed:publicationType
Journal Article