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A modular and adaptive framework for large scale video indexing and content‐based retrieval: the SIRSALE system
Author(s) -
Mostefaoui A.
Publication year - 2006
Publication title -
software: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.437
H-Index - 70
eISSN - 1097-024X
pISSN - 0038-0644
DOI - 10.1002/spe.722
Subject(s) - computer science , search engine indexing , modular design , adaptation (eye) , information retrieval , key (lock) , multimedia , world wide web , scale (ratio) , video retrieval , physics , computer security , quantum mechanics , optics , operating system
In this paper, we present the design and the implementation of SIRSALE: a distributed video data management system. SIRSALE allows users to manipulate video streams stored in large distributed repositories, i.e. it provides remote users with functionalities to browse video streams by structures (shots, scenes, sequences, etc.), to annotate the semantic contents of videos and to query the distributed video repositories. One of the main contributions of SIRSALE is its contextual adaptation to the target application, i.e. it is based on a modular data model that allows adapting the system to deal with several semantic contexts. In other words, SIRSALE allows users to define and to use their own semantic data model in order to annotate and query video databases. The key idea behind this is to dynamically adapt the whole system, mainly user interfaces, to stand several semantic data models. The system has been presented to professionals who gave a positive feedback. Copyright © 2006 John Wiley & Sons, Ltd.