Ana-Maria Manzat

Managing and querying efficiently distributed semantic multimedia metadata collections

Currently, many multimedia contents are acquired and stored in real time and on different locations. In order to retrieve efficiently the desired information and to avoid centralizing all metadata, we propose to compute a centralized metadata resume, i.e., a concise version of the whole metadata, which locates some desired multimedia contents on remote servers. The originality of this resume is that it is automatically constructed based on the extracted metadata. In this paper, we present a method to construct such resume and illustrate our framework with current Semantic Web technologies, such as RDF and SPARQL for representing and querying semantic metadata. Some experimental results are provided in order to show the benefits of indexing and retrieving multimedia contents without centralizing multimedia contents or their associated metadata, and to prove the efficiency of a metadata resume.

A distributed architecture for flexible multimedia management and retrieval

Developing an efficient system that manages distributed multimedia content supposes to minimize resource consumption while providing the most relevant results for a users 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.

Managing and Querying Distributed Multimedia Metadata

The authors propose an automatically constructed metadata resume to facilitate the retrieval of desired media information about content distributed across several servers.

A Generic Metadata Framework for the Indexation and the Management of Distributed Multimedia Contents

Currently, many multimedia contents are acquired and stored in real time and on different locations. These contents are indexed in order to provide some metadata that are used during the retrieval process. However, several existing metadata standards can be used for describing the content, and mixing them do not ensure interoperability. To overcome this problem, we propose in this paper a generic metadata framework that defines an abstract representation of a multimedia document and encapsulates the most common metadata standards.

A Framework for Automatizing and Optimizing the Selection of Indexing Algorithms

Inside an information system, the indexation process facilitates the retrieval of specific contents. However, this process is known as time and resource consuming. Simultaneously, the diversity of multimedia indexing algorithms is growing steeply which makes harder to select the best ones for particular user needs. In this article, we propose a generic framework which determines the most suitable indexing algorithms according to user queries, hence optimizing the indexation process. In this framework, the multimedia features are used to define multimedia metadata, user queries as well as indexing algorithm descriptions. The main idea is that, apart from retrieving contents, user queries could be also used to identify a relevant set of algorithms which detect the requested features. The application of our proposed framework is illustrated through the case of an RDF-based information system. In this case, our approach could be further optimized by a broader integration of Semantic Web technologies.

Adapting Indexation to the Content, Context and Queries Characteristics in Distributed Multimedia Systems

Due to the dramatically increasing amount of multimedia contents in several application domains, effective and flexible solutions for distributed data indexation are essential. In the management of these multimedia contents, the indexing process is the most important resource consumer, in terms of data transfer over the network and CPU consumption. As result of our research, we located two points for reducing resource consumption: the limitation of multimedia content transfer over the network for indexing, as well as the reduction of multimedia indexing amount by employing only the most appropriate algorithms for performing indexation, only over the relevant contents. We present in this paper the solution developed in the context of the LINDO project for indexing multimedia content into a distributed system that originally address these two points by reducing as much as possible the resource consumption through (1) a distributed indexing technique that avoids multimedia transfer, (2) a flexible mechanism for selecting the indexing algorithms to be employed on each remote server, according to the multimedia content characteristics, its acquisition context and user queries history.

Towards a Pervasive Access Control within Video Surveillance Systems

This paper addresses two emerging challenges that multimedia distributed systems have to deal with: the user’s constant mobility and the information’s sensitivity. The systems have to adapt, in real time, to the user’s context and situation in order to provide him with relevant results without breaking the security and privacy policies. Distributed multimedia systems, such as the oneproposed by the LINDO project, do not generally consider both issues. In this paper, we apply an access control layer on top of the LINDO architecture that takes into consideration the user’s context and situation and recommends alternative resources to the user when he is facing an important situation. The proposed solution was implemented and tested in a video surveillance use case.