Title
A comprehensive representation scheme for video semantic ontology and its applications in semantic concept detection
Abstract
Recent research has discovered that leveraging ontology is an effective way to facilitate semantic video concept detection. As an explicit knowledge representation, a formal ontology definition usually consists of a lexicon, properties, and relations. In this paper, we present a comprehensive representation scheme for video semantic ontology in which all the three components are well studied. Specifically, we leverage LSCOM to construct the concept lexicon, describe concept property as the weights of different modalities which are obtained manually or by data-driven approach, and model two types of concept relations (i.e., pairwise correlation and hierarchical relation). In contrast with most existing ontologies which are only focused on one or two components for domain-specific videos, the proposed ontology is more comprehensive and general. To validate the effectiveness of this ontology, we further apply it to video concept detection. The experiments on TRECVID 2005 corpus have demonstrated a superior performance compared to existing key approaches to video concept detection.
Year
DOI
Venue
2012
10.1016/j.neucom.2011.05.044
Neurocomputing
Keywords
Field
DocType
domain-specific video,formal ontology definition,existing ontology,concept lexicon,concept property,video semantic ontology,video concept detection,comprehensive representation scheme,semantic video concept detection,semantic concept detection,concept relation,proposed ontology,ontology
Ontology (information science),Ontology,Ontology-based data integration,Process ontology,Information retrieval,Computer science,Ontology Inference Layer,Formal ontology,Artificial intelligence,Natural language processing,Suggested Upper Merged Ontology,Upper ontology
Journal
Volume
ISSN
Citations 
95,
0925-2312
0
PageRank 
References 
Authors
0.34
14
5
Name
Order
Citations
PageRank
Zheng-Jun Zha12822152.79
Tao Mei24702288.54
Yan-Tao Zheng3179564.95
Zengfu Wang4113385.70
Xian-Sheng Hua56566328.17