Academic literature on the topic 'Multimedia documents'

Multimedia production is an elaborate activity composed of multiple information management and transformation tasks that support an underlying creative goal. Examples of these activities are structuring, organization, modification and versioning of media elements, all of which depend on the maintenance of supporting documentation and metadata. In professional productions, which can count on proper human and material resources, such documentation is maintained by the production crew, being key to secure a high quality in the final content. In less resourceful configurations, such as amateur-oriented productions, at least reasonable quality standards are desirable in most cases, however the perceived difficulty in managing and transforming content can inhibit amateurs on producing content with acceptable quality. This problem has been tackled in many fronts, for instance via annotation methods, smart browsing methods and authoring techniques, just to name a few. In this dissertation, the primary objective is to take advantage of user-created annotations in order to aid amateur-oriented multimedia authoring. In order to support this objective, the contributions are built around an authoring approach based on structured multimedia documents. First, a custom language for Web-based multimedia documents is defined, based on SMIL (Synchronized Multimedia Integration Language). This language brings several contributions, such as the formalization of an extended graph-based temporal layout model, live editing of document elements and extended reuse features. Second, a model for document annotation and an algebra for document transformations are defined, both of which allows composition and extraction of multimedia document fragments based on annotations. Third, the previous contributions are integrated into a Web-based authoring tool, which allows manipulating a document while it is active. Such manipulations encompass several interaction techniques for enriching, editing, publishing and extending multimedia documents. The contributions have been instantiated with multimedia sessions obtained from synchronous collaboration tools, in scenarios of video-based lectures, meetings and video-based qualitative research. Such instantiations demonstrate the applicability and utility of the contributions<br>Produção multimídia é uma atividade complexa composta por múltiplas atividades de gerência e transformação de informação, as quais suportam um objetivo de criar conteúdo. Exemplos dessas atividades são estruturação, organização, modificação e versionamento de elementos de mídia, os quais dependem da manutenção de documentos auxiliares e metadados. Em produções profissionais, as quais podem contar com recursos humanos e materiais adequados, tal documentação é mantida pela equipe de produção, sendo instrumental para garantir a uma alta qualidade no produto final. Em configurações com menos recursos, como produções amadoras, ao menos padrões razoáveis de qualidade são desejados na maioria dos casos, contudo a dificuldade em gerenciar e transformar conteúdo pode inibir amadores a produzir conteúdo com qualidade aceitável. Esse problema tem sido atacado em várias frentes, por exemplo via métodos de anotação, métodos de navegação e técnicas de autoria, apenas para nomear algumas. Nesta tese, o objetivo principal é tirar proveito de anotações criadas pelo usuário com o intuito de apoiar autoria multimídia por amadores. De modo a subsidiar esse objetivo, as contribuições são construídas em torno uma abordagem de autoria baseada em documentos multimídia estruturados. Primeiramente, uma linguagem customizada para documentos multimídia baseados na Web é definida, baseada na linguagem SMIL (Synchronized Multimedia Integration Language). Esta linguagem traz diversas contribuições, como a formalização de um modelo estendido para formatação temporal baseado em grafos, edição ao vivo de elementos de um documento e funcionalidades de reúso. Em segundo, um modelo para anotação de documentos e uma álgebra para transformação de documentos são definidos, ambos permitindo composição e extração de fragmentos de documentos multimídia com base em anotações. Em terceiro, as contribuições anteriores são integradas em uma ferramenta de autoria baseada na Web, a qual permite manipular um documento enquanto o mesmo está ativo. Tais manipulações envolvem diferentes técnicas de interação com o objetivo de enriquecer, editar, publicar e estender documentos multimídia interativos. As contribuições são instanciadas com sessões multimídia obtidas de ferramentas de colaboração síncrona, em cenários de aulas baseadas em vídeos, reuniões e pesquisa qualitativa baseada em vídeos. Tais instanciações demonstram a aplicabilidade e utilidade das contribuições

Multimedia documents are composed of multiple file format combinations, such as image and text, image and sound, or image, text and sound. The type of multimedia document determines the form of analysis for knowledge architecture design and retrieval methods. Over the last few decades, theories of text analysis have been proposed and applied effectively. In recent years, theories of image and sound analysis have been proposed to work with text retrieval systems and progressed quickly due in part to rapid progress in computer processing speed. Retrieval of multimedia documents formerly was divided into the categories of image and text, and image and sound. While standard retrieval process begins from text only, methods are developing that allow the retrieval process to be accomplished simultaneously using text and image. Although image processing for feature extraction and text processing for term extractions are well understood, there are no prior methods that can combine these two features into a single data structure. This dissertation will introduce a common representation format for multimedia documents (CRFMD) composed of both images and text. For image and text analysis, two techniques are used: the Lorenz Information Measurement and the Word Code. A new process named Jeong's Transform is demonstrated for extraction of text and image features, combining the two previous measurements to form a single data structure. Finally, this single data measurements to form a single data structure. Finally, this single data structure is analyzed by using multi-dimensional scaling. This allows multimedia objects to be represented on a two-dimensional graph as vectors. The distance between vectors represents the magnitude of the difference between multimedia documents. This study shows that image classification on a given test set is dramatically improved when text features are encoded together with image features. This effect appears to hold true even when the available text is diffused and is not uniform with the image features. This retrieval system works by representing a multimedia document as a single data structure. CRFMD is applicable to other areas of multimedia document retrieval and processing, such as medical image retrieval, World Wide Web searching, and museum collection retrieval.

Au cours de la dernière décennie, d'énormes quantités de documents multimédias ont été générées. Il est donc important de trouver un moyen de gérer ces données, notamment d'un point de vue sémantique, ce qui nécessite une connaissance fine de leur contenu. Il existe deux familles d'approches pour ce faire, soit par l'extraction d'informations à partir du document (par ex., audio, image), soit en utilisant des données textuelles extraites du document ou de sources externes (par ex., Web). Notre travail se place dans cette seconde famille d'approches ; les informations extraites des textes peuvent ensuite être utilisées pour annoter les documents multimédias et faciliter leur gestion. L'objectif de cette thèse est donc de développer de tels modèles d'extraction d'informations. Mais les textes extraits des documents multimédias étant en général petits et bruités, ce travail veille aussi à leur nécessaire robustesse. Nous avons donc privilégié des techniques simples nécessitant peu de connaissances externes comme garantie de robustesse, en nous inspirant des travaux en recherche d'information et en analyse statistique des textes. Nous nous sommes notamment concentré sur trois tâches : l'extraction supervisée de relations entre entités, la découverte de relations, et la découverte de classes d'entités. Pour l'extraction de relations, nous proposons une approche supervisée basée sur les modèles de langues et l'algorithme d'apprentissage des k-plus-proches voisins. Les résultats expérimentaux montrent l'efficacité et la robustesse de nos modèles, dépassant les systèmes état-de-l'art tout en utilisant des informations linguistiques plus simples à obtenir. Dans la seconde tâche, nous passons à un modèle non supervisé pour découvrir les relations au lieu d'en extraire des prédéfinies. Nous modélisons ce problème comme une tâche de clustering avec une fonction de similarité là encore basée sur les modèles de langues. Les performances, évaluées sur un corpus de vidéos de matchs de football, montrnt l'intérêt de notre approche par rapport aux modèles classiques. Enfin, dans la dernière tâche, nous nous intéressons non plus aux relations mais aux entités, source d'informations essentielles dans les documents. Nous proposons une technique de clustering d'entités afin de faire émerger, sans a priori, des classes sémantiques parmi celles-ci, en adoptant une représentation nouvelle des données permettant de mieux tenir compte des chaque occurrence des entités. En guise de conclusion, nous avons montré expérimentalement que des techniques simples, exigeant peu de connaissances a priori, et utilisant des informations linguistique facilement accessibles peuvent être suffisantes pour extraire efficacement des informations précises à partir du texte. Dans notre cas, ces bons résultats sont obtenus en choisissant une représentation adaptée pour les données, basée sur une analyse statistique ou des modèles de recherche d'information. Le chemin est encore long avant d'être en mesure de traiter directement des documents multimédia, mais nous espérons que nos propositions pourront servir de tremplin pour les recherches futures dans ce domaine.

L'énorme quantité de documents multimédias constamment générés incite au développement de méthodes d'analyse automatique. Dans ce cadre, notre objectif est de faciliter ce processus en extrayant des informations à partir de n'importe quel texte relatif à ces documents. En outre, nous voulons des techniques suffisamment robustes pour traiter des données bruitées et de petite taille. Pour ce faire, nous utilisons des techniques simples nécessitant peu de connaissances externes comme une garantie de robustesse. Plus précisément, nous utilisons des techniques inspirées de la recherche d'information et de l'analyse statistique. Dans cette thèse, nous montrons expérimentalement que des techniques simples, sans connaissance a priori peuvent être utiles pour extraire efficacement les informations à partir du texte. Dans notre cas, ces bons résultats ont été obtenus en choisissant une représentation adaptée pour les données au lieu d'exiger de traitements complexes<br>Due to the huge amounts of multimedia documents that have been generated, researchers studied approaches to manage them. Our goal is to facilitate this process by extracting information from any text related to such documents. Moreover, we want techniques robust enough to handle noisy and small data. We use simple and nowledge-light techniques as a guarantee of robustness. Indeed, we use statistical analysis of text and some techniques inspired from Information Retrieval. In this thesis, we experimentally show that simple techniques without a priori knowledge can be useful to effectively extract information from text. In our case, such results have indeed been achieved by choosing suited representation for the data instead of requiring complex processings

The growing importance of multimedia content generated by ordinary users demands research for models, methods, technologies and systems that support multimedia production. Despite recent results allowing the collaborative capture of video via mobile devices, there is gap in supporting the collaborative capture of multiple media. In this dissertation we propose that ubiquitous collaborative multimedia production can be carried out by users who capture and annotate multiple media using the CMoViA mobile application. CMoViA also allows export the user-generated content to the CI+WaC, which allows them to edit the user-generated content in the form of interactive and extensible multimedia documents. The proposal demanded extending recent work reported in the literature, namely the I+WaC-IE (Interactors+WaC-Interaction Events) model, the I+WaC-Editor tool and MoViA tool. Hence, CMoViA follows the proposed CI+WaC-IE model. We discuss results from a case study, carried out in the educational domain, in which students collaboratively capture a lecture.<br>A crescente importância de conteúdo multimídia gerado por usuários amadores exige pesquisas por modelos, métodos, tecnologias e sistemas que apoiem a produção multimídia. Apesar dos recentes resultados que permitem captura colaborativa em vídeo utilizando dispositivos móveis, existe uma lacuna no apoio à captura colaborativa de múltiplas mídias. O trabalho apresentado nesta dissertação propõe que a produção multimídia colaborativa ubíqua possa ser alcançada por usuários que realizem a captura de múltiplas mídias e de anotações utilizando o aplicativo móvel CMoViA. CMoViA também permite que o conteúdo gerado por esses usuários seja exportado para a plataforma CI+WaC, a qual permite editar e anotar documentos multimídia interativos. Essa proposta requer a extensão de trabalho recentes reportados na literatura: o modelo I+WaC-IE (Interactors+WaC-Interaction Events), a ferramenta I+WaC-Editor e a ferramenta MoViA. Assim, a aplicação CMoViA segue o modelo CI+WaC-IE proposto neste trabalho como extensão do modelo I+WaC-IE. A proposta foi avaliada por meio de estudo de caso realizado no domínio educacional, no qual estudantes capturam colaborativamente uma palestra.

The area of multimedia applications keeps growing as more media become accessible and affordable on various computer platforms. Through the use of multiple information channels, more effective and expressive communication among people using computers is possible. However, due to the lack of a systematic authoring environment, multimedia documents are difficult to construct and their production is unnecessarily constrained in the ways that temporal and spatial relationships within the document can be expressed, and in the ways which user interactions can be employed. In this dissertation, a number of techniques to enhance the multimedia authoring environment are presented. A hierarchical framework is provided to form the basic multimedia document structure and to support various media materials uniformly, including regular media as well as user interactions. Based on this framework a set of algorithms for low-level analysis and synthesis are developed to support high level authoring tools. Error checking such as resource conflict detection and resolution, as well as better understanding of a multimedia document therefore become possible. A number of flow control primitives have also been identified to support flexible user interactivity. Finally, mechanisms to realize a novel multimedia authoring approach, the walk-through paradigm, are developed. All these techniques are implemented and tested in a multimedia authoring prototype environment following object-oriented design principles. Together, these techniques support more interesting multimedia documents, better authoring aids and more friendly authoring environment. Better user interaction is possible in multimedia documents with flexible scheduling and presentation flow control. Interactively analyzing and modifying the document provides useful authoring support, and the walk-through mechanism supports an easy-to-use authoring tool.

Cette these debat du probleme du classement de l'information bureautique. Celle-ci se trouve sous forme de documents multimedia, c'est-a-dire que son contenu peut renfermer differents types de donnees; on y trouve du texte, du graphique, de l'image, des sequences sonores, etc. Un modele semantique a ete propose pour classer et/ou rechercher cette information. Il est base sur des mecanismes d'abstraction utilisant les notions de generalisation, de specialisation de regroupement, etc. L'approche orientee objet a ete utilisee pour definir les objets et les actions de classement. Le modele a ete valide par une realisation effectuee dans le cadre d'un systeme de gestion de documents multimedia au sein d'un systeme bureautique integre. Le modele relationnel a ete utilise comme noyau pour batir le systeme de classement