Conceptual structures: information processing in mind and machine
Conceptual structures: information processing in mind and machine
Scene change detection techniques for video database systems
Multimedia Systems
RELIEF: combining expressiveness and rapidity into a single system
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Querying virtual videos using path and temporal expressions
SAC '98 Proceedings of the 1998 ACM symposium on Applied Computing
The LIMSI Broadcast News transcription system
Speech Communication - Special issue on automatic transcription of broadcast news data
An Approach to a Content-Based Retrieval ofMultimedia Data
Multimedia Tools and Applications
Integrated Video and Text for Content-based Access to Video Databases
Multimedia Tools and Applications
Semantic Annotation of Sports Videos
IEEE MultiMedia
Annotation and retrieval of structured video documents
ECIR'03 Proceedings of the 25th European conference on IR research
VideoGraph: a graphical object-based model for representing and querying video data
ER'00 Proceedings of the 19th international conference on Conceptual modeling
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The growing need for ’intelligent’ video retrieval systems leads to new architectures combining multiple characterizations of the video content that rely on highly expressive frameworks while providing fully-automated indexing and retrieval processes. As a matter of fact, addressing the problem of combining modalities within expressive frameworks for video indexing and retrieval is of huge importance and the only solution for achieving significant retrieval performance. This paper presents a multi-facetted conceptual framework integrating multiple characterizations of the audio content for automatic video retrieval. It relies on an expressive representation formalism handling high-level audio descriptions of a video document and a full-text query framework in an attempt to operate video indexing and retrieval on audio features beyond state-of-the-art architectures operating on low-level features and keyword-annotation frameworks. Experiments on the multimedia topic search task of the TRECVID 2004 evaluation campaign validate our proposal.