A Distributed Architecture for Flexible Multimedia Management and Retrieval

Abstract

Developing an efficient system that manages distributed multimedia content supposes to minimize resource consumption while providing the most relevant results for a user's query in the shortest time. This paper presents LINDO, a generic architecture framework for distributed systems that acquires efficiency in multimedia indexing and retrieval. Three characteristics particularize it: (1) it differentiates between implicit algorithms executed over all the multimedia content at the acquisition time, and explicit algorithms, executed on demand for answering a specific need; (2) it stores and processes multimedia content and metadata locally, instead of transferring and indexing it on a central server; (3) it selects a set of relevant servers for query execution based on the user query semantic processing and on the system knowledge, including descriptions of distributed servers, multimedia content and indexing algorithms. The paper relies on a concrete implementation of the LINDO framework in order to validate this contribution.

A Distributed Framework for Content Search Using Small World Communities

“…In this work, too many local search services are connected to a global search service. Brut [5] has designed a framework that uses a central server and many remote ones. In this approach, a query is executed only on a set of relevant servers based on user queries, using semantic processing and available knowledge about the distributed servers, the multimedia content and the indexing algorithms.…”

“…These collections can be organized in many ways. In the large scale distributed indexation of multimedia objects (LINDO) system [5], there are some remote servers that store and index all acquired multimedia information. Some modules are used to manage all needed tasks such as the Storage Manager, the Access Manager, the Feature Extractor Manager, the Metadata Engine.…”

Towards a Pervasive Access Control within Video Surveillance Systems

“…DO project (Large scale distributed INDexation of multim a distributed system for multimedia content managem ficient use of the resources in the indexing and qu the multimedia contents storage is distributed, but also nality of this solution is that: moved to indexing servers, but the indexing algorithms emote servers where the content is acquired; cess is accomplished in two steps: at acquisition and on of the LINDO architecture can be found in [20]. esources consumption, the architecture allows the index be accomplished at acquisition time (i.e., implicit indexi ch extract generic features from the content (e.g., per detection) and on demand (i.e., explicit indexing) w ract more detailed features (e.g., person recognition, reg is avoids executing all the indexing algorithms at once ight never be used, but raises access rights issues conce the elect tion here could be some servers that contain relevant information that has not been indexed with the right algorithms.…”

“…The query is processed and translated into XQuery. This query transformation is detailed in [20]. The query processing begins by locating the servers responsible for managing the data captured by the cameras located in the bus nr 2, which passed between 14h00 and 15h00 at Place d'Italie station.…”

A distributed framework for multimedia using small world communities

“…In this work, too many local search services are connected to a global search service. Brut (Brut, Codreanu, & Dumitrescu, 2011) has designed a framework that uses a central server and many remote ones. In this approach, a query is executed only on a set of relevant servers based on user queries, using semantic processing and available knowledge about the distributed servers, the multimedia content and the indexing algorithms.…”