Paper Info
Title
A New Linguistic-Perceptual Event Model for Spatio-Temporal Event Detection and Personalized Retrieval of Sports Video
Abstract
This paper proposes a new linguistic-perceptual event model tailoring to spatio-temporal event detection and conceptual-visual personalized retrieval of sports video sequences. The major contributions of the proposed model are hierarchical structure, independence between linguistic and perceptual part, and ability of capturing temporal information of sports events. Thanks to these advanced contributions, it is very easy to upgrade model events from simple to complex levels either by self-studying from inner knowledge or by being taught from plug-in additional knowledge. Thus, the proposed model not only can work well in unwell structured environments but also is able to adapt itself to new domains without the need (or with a few modification) for external re-programming, re-configuring and re-adjusting. Thorough experimental results demonstrate that events are modeled and detected with high accuracy and automation, and users' expectation of personalized retrieval is highly satisfied.
Year
DOI
Venue
2009
10.1007/978-3-642-04146-4_64
ICIAP
Keywords
Field
DocType
new domain,conceptual-visual personalized retrieval,event detection,inner knowledge,spatio-temporal event detection,sports video,personalized retrieval,model event,new linguistic-perceptual event model,plug-in additional knowledge,sports event,string matching,satisfiability
String searching algorithm,Computer vision,Computer science,Event model,Multimedia information retrieval,Automation,Upgrade,Artificial intelligence,Perception,Linguistics,Machine learning,Personalization
Conference
Volume
ISSN
Citations 
5716
0302-9743
0
PageRank 
References 
Authors
0.34
9
3
Name
Order
Citations
PageRank
Minh-son Dao19321.42
Sharma Ishan Nath200.34
Noboru Babaguichi300.34