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.
A multimedia system needs a mechanism to communicate with its environment, the Internet, clients, and applications. MPEG-7 provides a standard metadata format for global communication, but lacks the framework to let the various players in a system interact. MPEG-21 closes this gap by establishing an infrastructure for a distributed multimedia frame
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.
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.
We welcomed participants to the 1st EurAsian Conference on Advances in Information and Communication Technology (EurAsia ICT 2002) held in Iran. The aim of the conference was to serve as a forum to bring together researchers from academia and commercial developers from industry to discuss the current state of the art in ICT, mainly in Europe and Asia. Inspirations and new ideas were expected to emerge from intensive discussions during formal sessions and social events. Keynote addresses, research presentation, and discussion during the conference helped to further develop the exchange of ideas among the researchers, developers, and practitioners who attended. The conference attracted more than 300 submissions and each paper was reviewed by at least three program committee members. The program committee selected 119 papers from authors of 30 different countries for presentation and publication, a task which was not easy due to the high quality of the submitted papers. Eleven workshops were organized in parallel with the EurAsia ICT conference. The proceedings of these workshops, with more than 100 papers, were published by the Austrian Computer Society. We would like to express our thanks to our colleagues who helped with putting together the technical program: the program committee members and external reviewers for their timely and rigorous reviews of the papers, and the organizing committee for their help in administrative work and support. We owe special thanks to Thomas Schierer for always being available when his helping hand was needed.
Content-Based Image And Video Retrieval addresses the basic concepts and techniques for designing content-based image and video retrieval systems. It also discusses a variety of design choices for the key components of these systems. This book gives a comprehensive survey of the content-based image retrieval systems, including several content-based video retrieval systems. The survey includes both research and commercial content-based retrieval systems. Content-Based Image And Video Retrieval includes pointers to two hundred representative bibliographic references on this field, ranging from survey papers to descriptions of recent work in the area, entire books and more than seventy websites. Finally, the book presents a detailed case study of designing MUSE–a content-based image retrieval system developed at Florida Atlantic University in Boca Raton, Florida.
Presently, in our world, visual information dominates. The turn of the millenium marks the age of visual information systems. Enabled by picture sensors of all kinds turning digital, visual information will not only enhance the value of existing information, it will also open up a new horizon of previously untapped information sources. There is a huge demand for visual information access from the consumer. As well, the handling of visual information is boosted by the rapid increase of hardware and Internet capabilities. Advanced technology for visual information systems is more urgently needed than ever before: not only new computational methods to retrieve, index, compress and uncover pictorial information, but also new metaphors to organize user interfaces. Also, new ideas and algorithms are needed which allow access to very large databases of digital pictures and videos. Finally we should not forget new systems with visual interfaces integrating the above components into new types of image, video or multimedia databases and hyperdocuments. All of these technologies will enable the construction of systems that are radically different from conventional information systems. Many novel issues will need to be addressed: query formulation for pictorial information, consistency management thereof, indexing and assessing the quality of these systems. Historically, the expression Visual Information Systems can be understood either as a system for image information or as visual system for any kind information.
-Presents state-of-the-art in visual media retrieval. -Coverage of adaptive content-based retrieval systems and techniques in image and video database applications. -Includes a novel machine-controlled interactive retrieval (MCIR) method that optimizes image search in distributed digital libraries over the Internet.
"This book summarizes theoretical studies and practical solutions for engineers, educational professionals, and graduate students in the research areas of e-learning, distance education, and instructional designs. Readers will find solutions and research directions in this interesting book"--Provided by publisher.
