SQL:1999 y SQL/MM para el modelado y diseño de bases de datos multimedia

Los datos multimedia son cada vez más comunes en las aplicaciones actuales, siendo tanto o más importante no sólo contar con la información textual, sino con la imagen que la representa. Estas aplicaciones que trabajan con distintos tipos de media: texto, imágenes, animaciones, video, audio, etc., requieren de un modelo de datos adecuado que represente la estructura y contenido de los datos y, posteriormente, un diseño de esquemas de bases de datos apropiado para el almacenamiento y recuperación de la información multimedia. El propósito principal de la investigación propuesta se basa en el empleo de SGBDOR comerciales y sus extensiones (SQL/MM) para la representación de datos multimedia, de modo que permitan implementar mecanismos adecuados de almacenamiento de datos multimedia, que faciliten la formulación de consultas y la recuperación de la información.Eje: Ingeniería de software y base de datosRed de Universidades con Carreras en Informática (RedUNCI

SQL:1999 y SQL/MM para el modelado y diseño de bases de datos multimedia

Los datos multimedia son cada vez más comunes en las aplicaciones actuales, siendo tanto o más importante no sólo contar con la información textual, sino con la imagen que la representa. Estas aplicaciones que trabajan con distintos tipos de media: texto, imágenes, animaciones, video, audio, etc., requieren de un modelo de datos adecuado que represente la estructura y contenido de los datos y, posteriormente, un diseño de esquemas de bases de datos apropiado para el almacenamiento y recuperación de la información multimedia. El propósito principal de la investigación propuesta se basa en el empleo de SGBDOR comerciales y sus extensiones (SQL/MM) para la representación de datos multimedia, de modo que permitan implementar mecanismos adecuados de almacenamiento de datos multimedia, que faciliten la formulación de consultas y la recuperación de la información.Eje: Ingeniería de software y base de datosRed de Universidades con Carreras en Informática (RedUNCI

A preliminary study of current multimedia information technology

This paper surveys more than 70 articles published in the IEEE Multimedia journal and other journals. The survey summarizes aspects of multimedia information technology and categorizes application areas of multimedia information technology and interesting research areas related to it

Event Based Retrieval From Digital Libraries Containing Data Streams

The objective of this research is to study the issues involved in building a digital library that contains data streams and allows event-based retrieval. “Digital Libraries are storehouses of information available through the Internet that provide ways to collect, store, and organize data and make it accessible for search, retrieval, and processing” [29]. Data streams are sources of information for applications such as news-on-demand, weather services, and scientific research, to name a few. A data stream is a sequence of data units produced over a period of time. Examples of data streams are video streams, audio stream, and sensor readings. Saving data streams in digital libraries is advantageous because of the services provided by digital libraries such as archiving, preservation, administration, and access control. Events are noteworthy occurrences that happen during data streams. Events are easier to remember than specific time instances at which they occur; hence using them for retrieval is more commensurate with human behavior and can be more efficient via direct accessing instead of scanning. The focus of this research is not only on storing data streams in a digital library and using event-based retrieval, but also on relating streams and playing them back at the same time, possibly in a synchronized manner, to facilitate better understanding in research or other working situations. Our approach for this research starts by considering digital libraries for: stock market, news streams, census bureau statistics, weather, sports games, and the educational environment. For each of these applications, we form categories of possible users and the basic requirements for each of them. As a result, we identify a list of design goals that we take into consideration in developing the architecture of the library. To illustrate and validate our approach we implement a medical digital library containing actual Computed Tomography (CT) scan streams. It also contains sample medical text and audio streams to show the heterogeneity of the library. Streams are displayed in a concise, yet complete, way that makes it unproblematic for users to decide whether or not to playback a stream and to set playback options. The playback interface itself is organized in a way that accommodates synchronous and asynchronous streams and enables users to control the playback of these streams. We study the performance of the specialized search and retrieval processes in comparison to traditional search and retrieval processes. We conclude with a discussion on how to adapt the library to additional stream types in addition to suggesting other future efforts in this area

Highly efficient low-level feature extraction for video representation and retrieval.

PhDWitnessing the omnipresence of digital video media, the research community has raised the question of its meaningful use and management. Stored in immense multimedia databases, digital videos need to be retrieved and structured in an intelligent way, relying on the content and the rich semantics involved. Current Content Based Video Indexing and Retrieval systems face the problem of the semantic gap between the simplicity of the available visual features and the richness of user semantics. This work focuses on the issues of efficiency and scalability in video indexing and retrieval to facilitate a video representation model capable of semantic annotation. A highly efficient algorithm for temporal analysis and key-frame extraction is developed. It is based on the prediction information extracted directly from the compressed domain features and the robust scalable analysis in the temporal domain. Furthermore, a hierarchical quantisation of the colour features in the descriptor space is presented. Derived from the extracted set of low-level features, a video representation model that enables semantic annotation and contextual genre classification is designed. Results demonstrate the efficiency and robustness of the temporal analysis algorithm that runs in real time maintaining the high precision and recall of the detection task. Adaptive key-frame extraction and summarisation achieve a good overview of the visual content, while the colour quantisation algorithm efficiently creates hierarchical set of descriptors. Finally, the video representation model, supported by the genre classification algorithm, achieves excellent results in an automatic annotation system by linking the video clips with a limited lexicon of related keywords

A Data Model for Exploration of Temporal Virtual Reality Geographic Information Systems

Geographic information systems deal with the exploration, analysis, and presentation of geo-referenced data. Virtual reality is a type of human-computer interface that comes close to the way people perceive information in the real world. Thus, virtual reality environments become the natural paradigm for extending and enhancing the presentational and exploratory capability of GIs applications in both the spatial and temporal domains. The main motivation of this thesis is the lack of a framework that properly supports the exploration of geographic information in a multi-dimensional and multi-sensorial environment (i.e., temporal virtual reality geographic information systems). This thesis introduces a model for virtual exploration of animations. Virtual exploration of animations is a framework composed of abstract data types and a user interface that allow non-expert users to control, manipulate, analyze, and present objects\u27 behaviors in a virtual-reality environment. In the model for virtual exploration of animations, the manipulation of the dynamic environment is accomplished through a set of operations performed over abstractions that represent temporal characteristics of actions. An important feature of the model is that the temporal information is treated as first-class entities and not as a mere attribute of action\u27s representations. Therefore, entities of the temporal model have their own built-in functionality and are able to represent complex temporal structures. In an environment designed for the manipulation of the temporal characteristics of actions, the knowledge of relationships among objects\u27 behaviors plays a significant role in the model. This information comes from the knowledge base of the application domain and is represented in the model through constraints among entities of the temporal model. Such constraints vary from simply relating the end points of two intervals to a complex mechanism that takes into account all relations between sequences of intervals of cyclic behaviors. The fact that the exploration of the information takes place in a virtual reality environment imposes new requirements on the animation model. This thesis introduces a new classification of objects in a VR environment and describes the associated semantics of each element in the taxonomy. These semantics are used to direct the way an object interacts with an observer and with other objects in the environment

A full-scale semantic content-based model for interactive multimedia information systems.

Issues of syntax have dominated research in multimedia information systems (MMISs), with video developing as a technology of images and audio as one of signals. But when we use video and audio, we do so for their content. This is a semantic issue. Current research in multimedia on semantic content-based models has adopted a structure-oriented approach, where video and audio content is described on a frame-by-frame or segment-by-segment basis (where a segment is an arbitrary set of contiguous frames). This approach has failed to cater for semantic aspects, and thus has not been fully effective when used within an MMIS. The research undertaken for this thesis reveals seven semantic aspects of video and audio: (1) explicit media structure; (2) objects; (3) spatial relationships between objects; (4) events and actions involving objects; (5) temporal relationships between events and actions; (6) integration of syntactic and semantic information; and (7) direct user-media interaction. This thesis develops a full-scale semantic content-based model that caters for the above seven semantic aspects of video and audio. To achieve this, it uses an entities of interest approach, instead of a structure-oriented one, where the MMIS integrates relevant semantic content-based information about video and audio with information about the entities of interest to the system, e.g. mountains, vehicles, employees. A method for developing an interactive MMIS that encompasses the model is also described. Both the method and the model are used in the development of ARISTOTLE, an interactive instructional MMIS for teaching young children about zoology, in order to demonstrate their operation

Indexation sémantique des images et des vidéos par apprentissage actif

Le cadre général de cette thèse est l'indexation sémantique et la recherche d'informations, appliquée à des documents multimédias. Plus précisément, nous nous intéressons à l'indexation sémantique des concepts dans des images et vidéos par les approches d'apprentissage actif, que nous utilisons pour construire des corpus annotés. Tout au long de cette thèse, nous avons montré que les principales difficultés de cette tâche sont souvent liées, en général, à l'fossé sémantique. En outre, elles sont liées au problème de classe-déséquilibre dans les ensembles de données à grande échelle, où les concepts sont pour la plupart rares. Pour l'annotation de corpus, l'objectif principal de l'utilisation de l'apprentissage actif est d'augmenter la performance du système en utilisant que peu d'échantillons annotés que possible, ainsi minimisant les coûts de l'annotations des données (par exemple argent et temps). Dans cette thèse, nous avons contribué à plusieurs niveaux de l'indexation multimédia et nous avons proposé trois approches qui succèdent des systèmes de l'état de l'art: i) l'approche multi-apprenant (ML) qui surmonte le problème de classe-déséquilibre dans les grandes bases de données, ii) une méthode de reclassement qui améliore l'indexation vidéo, iii) nous avons évalué la normalisation en loi de puissance et de l'APC et a montré son efficacité dans l'indexation multimédia. En outre, nous avons proposé l'approche ALML qui combine le multi-apprenant avec l'apprentissage actif, et nous avons également proposé une méthode incrémentale qui accélère l'approche proposé (ALML). En outre, nous avons proposé l'approche de nettoyage actif, qui aborde la qualité des annotations. Les méthodes proposées ont été tous validées par plusieurs expériences, qui ont été menées et évaluées sur des collections à grande échelle de l'indice de benchmark internationale bien connue, appelés TRECVID. Enfin, nous avons présenté notre système d'annotation dans le monde réel basé sur l'apprentissage actif, qui a été utilisé pour mener les annotations de l'ensemble du développement de la campagne TRECVID en 2011, et nous avons présenté notre participation à la tâche d'indexation sémantique de cette campagne, dans laquelle nous nous sommes classés à la 3ème place sur 19 participants.The general framework of this thesis is semantic indexing and information retrieval, applied to multimedia documents. More specifically, we are interested in the semantic indexing of concepts in images and videos by the active learning approaches that we use to build annotated corpus. Throughout this thesis, we have shown that the main difficulties of this task are often related, in general, to the semantic-gap. Furthermore, they are related to the class-imbalance problem in large scale datasets, where concepts are mostly sparse. For corpus annotation, the main objective of using active learning is to increase the system performance by using as few labeled samples as possible, thereby minimizing the cost of labeling data (e.g. money and time). In this thesis, we have contributed in several levels of multimedia indexing and proposed three approaches that outperform state-of-the-art systems: i) the multi-learner approach (ML) that overcomes the class-imbalance problem in large-scale datasets, ii) a re-ranking method that improves the video indexing, iii) we have evaluated the power-law normalization and the PCA and showed its effectiveness in multimedia indexing. Furthermore, we have proposed the ALML approach that combines the multi-learner with active learning, and also proposed an incremental method that speeds up ALML approach. Moreover, we have proposed the active cleaning approach, which tackles the quality of annotations. The proposed methods were validated through several experiments, which were conducted and evaluated on large-scale collections of the well-known international benchmark, called TrecVid. Finally, we have presented our real-world annotation system based on active learning, which was used to lead the annotations of the development set of TrecVid 2011 campaign, and we have presented our participation at the semantic indexing task of the mentioned campaign, in which we were ranked at the 3rd place out of 19 participants.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Research on manifold utilization of multi-viewpoint videos

制度:新 ; 文部省報告番号:甲2109号 ; 学位の種類:博士(国際情報通信学) ; 授与年月日:2005/8/24 ; 早大学位記番号:新408