For database designers, developers, and analysts or for anyone looking to catalog their exploding multimedia holdings. DLC: Multimedia systems.

The Handbook of Multimedia Information Management

Computers & Technology

Jain, Ramesh

Mehrotra, Rajiv

Grosky, William T.

Ramesh, Jain

Web Development & Design

PRENTICE/HALL

Humans are the best functioning example of multimedia communication and computing - that is, we understand information and experiences through the unified perspective offered by our five senses. This innovative textbook presents emerging techniques in multimedia computing from an experiential perspective in which each medium - audio, images, text, and so on - is a strong component of the complete, integrated exchange of information or experience. The authors' goal is to present current techniques in computing and communication that will lead to the development of a unified and holistic approach to computing using heterogeneous data sources. Gerald Friedland and Ramesh Jain introduce the fundamentals of multimedia computing, describing the properties of perceptually encoded information, presenting common algorithms and concepts for handling it, and outlining the typical requirements for emerging applications that use multifarious information sources. Designed for advanced undergraduate and beginning graduate courses, the book will also serve as an introduction for engineers and researchers interested in understanding the elements of multimedia and their role in building specific applications.

Multimedia Computing

Friedland, Gerald

Cambridge University Press

The seven chapters in this book (a companion to Computer vision: advances and applications , IEEE Computer Society Press) introduce the fundamental computer vision topics of image formation, segmentation, feature extraction and matching, constraint exploitation and shape recovery, three-dimensional object recognition, dynamic vision, and knowledge-based vision. Each chapter begins with an introductory tutorial, followed by a collection of key (previously published) papers covering the topics presented in the tutorial. The epilogue presents current research trends and future directions for computer vision. The bibliography lists selected papers published since 1980. Annotation copyright Book News, Inc. Portland, Or.

Computer Vision: Principles (IEEE COMPUTER SOCIETY PRESS TUTORIAL)

Kasturi, Rangachar

Computer Science

IEEE Computer Society

Event Mining for Explanatory Modeling (ACM Books)

This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert's knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.

Jalali, Laleh

Networking & Cloud Computing

Association for Computing Machinery

This book introduces the concept of Event Mining for building explanatory models from analyses of correlated data. Such a model may be used as the basis for predictions and corrective actions. The idea is to create, via an iterative process, a model that explains causal relationships in the form of structural and temporal patterns in the data. The first phase is the data-driven process of hypothesis formation, requiring the analysis of large amounts of data to find strong candidate hypotheses. The second phase is hypothesis testing, wherein a domain expert's knowledge and judgment is used to test and modify the candidate hypotheses. The book is intended as a primer on Event Mining for data-enthusiasts and information professionals interested in employing these event-based data analysis techniques in diverse applications. The reader is introduced to frameworks for temporal knowledge representation and reasoning, as well as temporal data mining and pattern discovery. Also discussed are the design principles of event mining systems. The approach is reified by the presentation of an event mining system called EventMiner, a computational framework for building explanatory models. The book contains case studies of using EventMiner in asthma risk management and an architecture for the objective self. The text can be used by researchers interested in harnessing the value of heterogeneous big data for designing explanatory event-based models in diverse application areas such as healthcare, biological data analytics, predictive maintenance of systems, computer networks, and business intelligence.

ACM Books

With the proliferation of citizen reporting, smart mobile devices, and social media, an increasing number of people are beginning to generate information about events they observe and participate in. A significant fraction of this information contains multimedia data to share the experience with their audience. A systematic information modeling and management framework is necessary to capture this widely heterogeneous, schemaless, potentially humongous information produced by many different people. This book is an attempt to examine the modeling, storage, querying, and applications of such an event management system in a holistic manner. It uses a semantic-web style graph-based view of events, and shows how this event model, together with its query facility, can be used toward emerging applications like semi-automated storytelling.  Table of Contents: Introduction / Event Data Models / Implementing an Event Data Model / Querying Events / Storytelling with Events / An Emerging Application / Conclusion

Managing Event Information: Modeling, Retrieval, and Applications (Synthesis Lectures on Data Management, 19)

Gupta, Amarnath

Morgan & Claypool Publishers

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