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Both the way we look at data, through a DBMS, and the nature of
data we ask a DBMS to manage have drastically evolved over the last
decade, moving from text to images (and to sound to a lesser
extent). Visual representations are used extensively within new
user interfaces. Powerful visual approaches are being experimented
for data manipulation, including the investigation of three
dimensional display techniques. Similarly, sophisticated data
visualization techniques are dramatically improving the
understanding of the information extracted from a database. On the
other hand, more and more applications use images as basic data or
to enhance the quality and richness of data manipulation services.
Image management has opened a wide area of new research topics in
image understanding and analysis. The IFIP 2.6 Working Group on
Databases strongly believes that a significant mutual enrichment is
possible by confronting ideas, concepts and techniques supporting
the work of researcher and practitioners in the two areas of visual
interfaces to DBMS and DBMS management of visual data. For this
reason, IFIP 2.6 has launched a series of conferences on Visual
Database Systems. The first one has been held in Tokyo, 1989. VDB-2
was held in Budapest, 1991. This conference is the third in the
series. As the preceding editions, the conference addresses
researchers and practitioners active or interested in user
interfaces, human-computer communication, knowledge representation
and management, image processing and understanding, multimedia
database techniques and computer vision.
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
Motion-based recognition deals with the recognition of an object
and/or its motion, based on motion in a series of images. In this
approach, a sequence containing a large number of frames is used to
extract motion information. The advantage is that a longer sequence
leads to recognition of higher level motions, like walking or
running, which consist of a complex and coordinated series of
events. Unlike much previous research in motion, this approach does
not require explicit reconstruction of shape from the images prior
to recognition. This book provides the state-of-the-art in this
rapidly developing discipline. It consists of a collection of
invited chapters by leading researchers in the world covering
various aspects of motion-based recognition including lipreading,
gesture recognition, facial expression recognition, gait analysis,
cyclic motion detection, and activity recognition. Audience: This
volume will be of interest to researchers and post- graduate
students whose work involves computer vision, robotics and image
processing.
Motion-based recognition deals with the recognition of an object
and/or its motion, based on motion in a series of images. In this
approach, a sequence containing a large number of frames is used to
extract motion information. The advantage is that a longer sequence
leads to recognition of higher level motions, like walking or
running, which consist of a complex and coordinated series of
events. Unlike much previous research in motion, this approach does
not require explicit reconstruction of shape from the images prior
to recognition. This book provides the state-of-the-art in this
rapidly developing discipline. It consists of a collection of
invited chapters by leading researchers in the world covering
various aspects of motion-based recognition including lipreading,
gesture recognition, facial expression recognition, gait analysis,
cyclic motion detection, and activity recognition. Audience: This
volume will be of interest to researchers and post- graduate
students whose work involves computer vision, robotics and image
processing.
Both the way we look at data, through a DBMS, and the nature of
data we ask a DBMS to manage have drastically evolved over the last
decade, moving from text to images (and to sound to a lesser
extent). Visual representations are used extensively within new
user interfaces. Powerful visual approaches are being experimented
for data manipulation, including the investigation of three
dimensional display techniques. Similarly, sophisticated data
visualization techniques are dramatically improving the
understanding of the information extracted from a database. On the
other hand, more and more applications use images as basic data or
to enhance the quality and richness of data manipulation services.
Image management has opened a wide area of new research topics in
image understanding and analysis. The IFIP 2.6 Working Group on
Databases strongly believes that a significant mutual enrichment is
possible by confronting ideas, concepts and techniques supporting
the work of researcher and practitioners in the two areas of visual
interfaces to DBMS and DBMS management of visual data. For this
reason, IFIP 2.6 has launched a series of conferences on Visual
Database Systems. The first one has been held in Tokyo, 1989. VDB-2
was held in Budapest, 1991. This conference is the third in the
series. As the preceding editions, the conference addresses
researchers and practitioners active or interested in user
interfaces, human-computer communication, knowledge representation
and management, image processing and understanding, multimedia
database techniques and computer vision.
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.
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.
The word multimedia is often associated with specific applications
from entertainment to web design to video to music. 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. 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. The goal of this book 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. The authors 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."
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