Candela-Storage, Analysis and Retrieval of Video Content in Distributed Systems: Real-Time Video Surveillance and Retrieval

Jaspers, E.G.T.; Wijnhoven, Rob G. J.; Albers, A.H.R.; Desurmont, Xavier; Barais, Maximilian; Hamaide, Julien; Lienard, Bruno

doi:10.1109/icme.2005.1521730

Cited by 6 publications

(4 citation statements)

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“…One growing technology for ontology usage is the W3C recommendation [8] called Resource Description Framework (RDF) which is a formal XML representation of entities (defined by a lot of triplets subject -predicate -object). Note that usage of MPEG-7 [2] is possible but too limited to the multi-media world, whereas RDF is more generalist. Because it is basically designed to manage meta-data, RDF is becoming a reference in knowledge management systems, and thus by extension it can be used as design of data warehouse because it provides a formal (and homogeneous) representation of data.…”

Section: Ontology and Graph Modelling Of The Knowledgementioning

confidence: 99%

“…When sensor B creates a new object O related to the newly detected element, the resolution mechanism is able to change the RDF graph of object O and it is directly changed in the object O itself to reflect the correct representation. The remote procedure call feature, also embedded in the core system software, is based upon Simple Objet Access Protocol (SOAP) which is already used in [1] and [2] for real-time (or near to) purpose. Moreover, since RDF is a XML based technology, usage of SOAP reduces some encoding issues.…”

Section: System Integrationmentioning

confidence: 99%

“…Applications are now able to give these kinds of outputs but they are often used only for search and retrieval and data is not re-exploited by applications themselves. Many works and technologies on video meta-data generation and storage features already exist [2] and one is now able to create efficient multimedia databases [3] using state of the art methodology such as Ontology [4] to process video data. A new problem that appears is how to manage this huge amount of generated meta-data to become a decision support system.…”

Section: Introductionmentioning

confidence: 99%

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Real-time high-level video understanding using data warehouse

et al. 2006

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High-level Video content analysis such as video-surveillance is often limited by computational aspects of automatic image understanding, i.e. it requires huge computing resources for reasoning processes like categorization and huge amount of data to represent knowledge of objects, scenarios and other models.This article explains how to design and develop a "near real-time adaptive image datamart", used, as a decisional support system for vision algorithms, and then as a mass storage system. Using RDF specification as storing format of vision algorithms meta-data, we can optimise the data warehouse concepts for video analysis, add some processes able to adapt the current model and pre-process data to speed-up queries. In this way, when new data is sent from a sensor to the data warehouse for long term storage, using remote procedure call embedded in object-oriented interfaces to simplified queries, they are processed and in memory data-model is updated. After some processing, possible interpretations of this data can be returned back to the sensor.To demonstrate this new approach, we will present typical scenarios applied to this architecture such as people tracking and events detection in a multi-camera network. Finally we will show how this system becomes a high-semantic data container for external data-mining.

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Section: Ontology and Graph Modelling Of The Knowledgementioning

confidence: 99%

Section: System Integrationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Real-time high-level video understanding using data warehouse

et al. 2006

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“…Le projet CANDELA 3 (Content Analysis and Network DELivery Architectures) se focalise sur l'analyse et la recherche du contenu vidéo dans plusieurs domaines (e.g., vidéosurveillance (Jaspers et al, 2005), vidéos personnelles (Pietarila et al, 2005)). L'architecture utilisée par le projet est composée par un serveur central qui contient tous les services mis à disposition de l'utilisateur, et où le contenu multimédia est téléchargé pour être indexé, et des serveurs qui n'ont comme but que de stocker les métadonnées générées par l'indexation (Petkovic and Jonker, 2005).…”

Section: Systèmes Multimédias Distribuésunclassified

Vers une vision pervasive d’un système de vidéosurveillance distribué. Extension en vue d'un contrôle d'accès adaptatif

Kukhun¹,

Codreanu²,

Manzat³

et al. 2013

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RESUME. LINDO est un projet visant à proposer un système de gestion de contenus multimédias distribués, ense focalisant sur leur indexation, stockage et recherche avec une contrainte de minimisation de la consommation des ressources. Cet objectif est réalisé par l'implémentation d'une technique d'indexation différée et distribuée des contenus. Dans le contexte dans lequel l'utilisateur est de plus en plus mobile et les données de plus en plus sensibles, le besoin d'ajouter une couche du contrôle d'accès émerge. Ce control d'accès peut engendrer un refus d'accès aux contenus, si l'utilisateur n'a pas les droits d'accès, ce qui peut être inconvénient dans certaines situations. Dans ce papier, nous abordons ces problèmes du refus d'accès et proposons d'appliquer un mécanisme adaptatif qui réécrit les requêtes d'accès en prenant en compte le contexte de l'utilisateur et sa situation. Notre proposition est basée sur l'architecture PSQRS qui assure l'accès aux ressources dans des contextes pervasifs. Le PSQRS utilise le modèle RBAC et le standard XACML.ABSTRACT. The LINDO project proposes an open system dedicated for managing distributed multimedia contents by focusing on their indexing, storage and retrieval. The objective is to provide efficient information retrieval with minimal processing costs. This was achieved through the proposal of an efficient decentralized content indexing mechanism. Considering a pervasive context, where users are mobile and acquire access to sensitive data sources, adding an access control layer on top of the LINDO architecture becomes essential. In this paper, we confront the access denial problems and we propose to apply an adaptive mechanism that rewrites access requests while considering the user's context and situational information. This operation is performed through PSQRS, a query-rewriting system that manages access based on the RBAC model and realizes decision-making using XACML.

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Smart search & retrieval on video databases

Albers

Wijnhoven

Jaspers³

2006 Digest of Technical Papers International Conference on Consumer Electronics

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Candela-Storage, Analysis and Retrieval of Video Content in Distributed Systems: Real-Time Video Surveillance and Retrieval

Cited by 6 publications

References 10 publications

Real-time high-level video understanding using data warehouse

Real-time high-level video understanding using data warehouse

Vers une vision pervasive d’un système de vidéosurveillance distribué. Extension en vue d'un contrôle d'accès adaptatif

Smart search & retrieval on video databases

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