Paper Info
Title
Ontology-supported video modeling and retrieval
Abstract
Current solutions are still far from reaching the ultimate goal, namely to enable users to retrieve the desired video clip among massive amounts of visual data in a semantically meaningful manner. With this study we propose a video database model that provides nearly automatic object, event and concept extraction. It provides a reasonable approach to bridging the gap between low-level representative features and high-level semantic contents from a human point of view. By using training sets and expert opinions, low-level feature values for objects and relations between objects are determined. At the top level we have an ontology of objects, events and concepts. Objects and/or events use all these information to generate events and concepts. The system has a reliable video data model, which gives the user the ability to make ontology-supported fuzzy querying. Queries containing objects, events, spatio-temporal clauses, concepts and low-level features can be handled.
Year
DOI
Venue
2006
10.1007/978-3-540-71545-0_3
Adaptive Multimedia Retrieval
Keywords
Field
DocType
visual data,video clip,video database model,low-level representative feature,ontology-supported video modeling,automatic object,low-level feature,reliable video data model,current solution,low-level feature value,concept extraction,data model
Video modeling,Data mining,Ontology,Information retrieval,Database model,Computer science,Bridging (networking),Fuzzy logic,Video tracking,Concept extraction,Data model
Conference
Volume
ISSN
Citations 
4398
0302-9743
2
PageRank 
References 
Authors
0.38
13
2
Name
Order
Citations
PageRank
Yakup Yildirim1323.00
Adnan Yazici264956.29