Multimedia Databases And Image Communication

Multimedia technologies are rapidly attracting more and more interest every day. The Internet as seen from the end user is one of the reasons for this phenomenon, but not the only one. Video on Demand is one of the buzzwords today, but its real availability to the general public is yet to come. Content providers – such as publishers, broadcasting companies, and audio/video production ?rms – must be able to archive and index their productions for later retrieval. This is a formidable task, even more so when the material to be sorted encompasses many di?erent types of several media and covers a time span of several years. In order for such a vast amount of data to be easily available, existing database design models and indexing methodologies have to be improved and re?ned. In addition, new techniques especially tailored to the various types of multimedia must be devised and evaluated. For archiving and trasmission, data compression is another issue that needs to be addressed. In many cases, it has been found that compression and indexing can be successfully integrated, since compressing the data by ?ltering out irrelevancy implies some degree of und- standing of the content structure.

There is a strong need for advances in the fields of image indexing and retrieval and visual query languages for multimedia databases. Image technology is facing both classical and novel problems for the organization and filtering of increasingly large amounts of pictorial data. Novel kinds of problems, such as indexing and high-level content-base, accessing to image databases, human interaction with multimedia systems, approaches to multimedial data, biometrics, data mining, computer graphics and augmented reality, have grown into real-life issues. The papers in this proceedings volume relate to the subject matter of multimedia databases and image communication. They offer different approaches which help to keep the field of research lively and interesting. Contents:A Context-Aware Framework for Multimodal Document Databases (A Celentano & O Gaggi)Endowing Geographic Information Systems with a Cognitive Level (A De Simone et al.)A Simple Fuzzy Extension to the Search of Documents on the Web (L Ďi Lascio et al.)Developing a System for the Retrieval of Melodies from Web Repositories (R Distasi et al.)Fast Face Recognition Using Fractal Range/Domain Classification (D Riccio)A Method for 3D Face Recognition Based on Mesh Normals (S Ricciardi & G Sabatino)High-D Data Visualization Methods via Probabilistic Principal Surfaces for Data Mining Applications (A Staiano et al.)A Study on Recovering the Cloud-Top Height from Infra-Red Video Sequences (A Anzalone et al.)Powerful Tools for Data Mining: Fractals, Power Laws, SVD and More (C Faloutsos)An Unsupervised Shot Classification System for News Video Story Detection (M De Santo et al.)3D-TV — The Future of Visual Entertainment (M A Magnor)Entropy as a Feature in the Analysis and Classification of Signals (A Casanova et al.) Readership: Academics and researchers in databases and communication. Keywords:Multimedia Databases;Indexing and High-Level Content-Based;Data Mining;Biometrics;Computer Graphics and Augmented Reality

Multimedia technologies are rapidly attracting more and more interest every day. The Internet as seen from the end user is one of the reasons for this phenomenon, but not the only one. Video on Demand is one of the buzzwords today, but its real availability to the general public is yet to come. Content providers – such as publishers, broadcasting companies, and audio/video production ?rms – must be able to archive and index their productions for later retrieval. This is a formidable task, even more so when the material to be sorted encompasses many di?erent types of several media and covers a time span of several years. In order for such a vast amount of data to be easily available, existing database design models and indexing methodologies have to be improved and re?ned. In addition, new techniques especially tailored to the various types of multimedia must be devised and evaluated. For archiving and trasmission, data compression is another issue that needs to be addressed. In many cases, it has been found that compression and indexing can be successfully integrated, since compressing the data by ?ltering out irrelevancy implies some degree of und- standing of the content structure.

Business intelligence has always been considered an essential ingredient for success. However, it is not until recently that the technology has enabled organizations to generate and deploy intelligence for global competition. These technologies can be leveraged to create the intelligent enterprises of the 21st century that will not only provide excellent and customized services to their customers, but will also create business efficiency for building relationships with suppliers and other business partners on a long term basis. Creating such intelligent enterprises requires the understanding and integration of diverse enterprise components into cohesive intelligent systems. Anticipating that future enterprises need to become intelligent, Intelligent Enterprises of the 21st Century brings together the experiences and knowledge from many parts of the world to provide a compendium of high quality theoretical and applied concepts, methodologies, and techniques that help diffuse knowledge and skills required to create and manage intelligent enterprises of the 21st century for gaining sustainable competitive advantage in a global environment. This book is a comprehensive compilation of the state of the art vision and thought processes needed to design and manage globally competitive business organizations.

As consumer costs for multimedia devices such as digital cameras and Web phones have decreased and diversity in the market has skyrocketed, the amount of digital information has grown considerably. Intelligent Multimedia Databases and Information Retrieval: Advancing Applications and Technologies details the latest information retrieval technologies and applications, the research surrounding the field, and the methodologies and design related to multimedia databases. Together with academic researchers and developers from both information retrieval and artificial intelligence fields, this book details issues and semantics of data retrieval with contributions from around the globe. As the information and data from multimedia databases continues to expand, the research and documentation surrounding it should keep pace as best as possible, and this book provides an excellent resource for the latest developments.

"This book presents the latest developments in computer vision methods applicable to various problems in multimedia computing, including new ideas, as well as problems in computer vision and multimedia computing"--Provided by publisher.

In the last few years we have observed an explosive growth of multimedia computing, communication and applications. This revolution is transforming the way people live, work, and interact with each other, and is impacting the way business, government services, education, entertainment and healthcare are operating. Yet, several issues related to modeling, specification, analysis and design of distributed multimedia database systems and multimedia information retrieval are still challenging to both researchers and praclitioners. Distributed Multimedia Databases: Techniques and Applications points out these challenges and provides valuable suggestions toward the necessary solutions, by focusing on multimedia database techniques.

This book constitutes the refereed proceedings of the International Conference on Image and Video Retrieval, CIVR 2002, held in London, UK, in July 2002.The 30 revised full papers presented together with an introduction by the volume editors were carefully reviewed and selected from 82 submissions. The papers are organized in topical sections on image retrieval, modeling, feature-based retrieval, semantics and learning, video retrieval, and evaluation and benchmarking.