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Books > Computing & IT > Applications of computing > Databases
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Content-Based Video Retrieval - A Database Perspective (Hardcover, 2004 ed.)
Loot Price: R2,967
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Content-Based Video Retrieval - A Database Perspective (Hardcover, 2004 ed.)
Series: Multimedia Systems and Applications, 25
Expected to ship within 10 - 15 working days
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Recent advances in computing, communication, and data storage have
led to an increasing number of large digital libraries publicly
available on the Internet. In addition to alphanumeric data, other
modalities, including video play an important role in these
libraries. Ordinary techniques will not retrieve required
information from the enormous mass of data stored in digital video
libraries. Instead of words, a video retrieval system deals with
collections of video records. Therefore, the system is confronted
with the problem of video understanding. The system gathers key
information from a video in order to allow users to query semantics
instead of raw video data or video features. Users expect tools
that automatically understand and manipulate the video content in
the same structured way as a traditional database manages numeric
and textual data. Consequently, content-based search and retrieval
of video data becomes a challenging and important problem.
This book focuses particularly on content-based video retrieval.
After addressing basic concepts and techniques in the field,
Content-Based Video Retrieval: A Database Perspective concentrates
on the semantic gap problem, i.e., the problem of inferring
semantics from raw video data, as the main problem of content-based
video retrieval. This book identifies and proposes the integrated
use of three different techniques to bridge the semantic gap,
namely, spatio-temporal formalization methods, hidden Markov
models, and dynamic Bayesian networks. As the problem is approached
from a database perspective, the emphasis evolves from a database
management system into a video database management system. This
system allows a user to retrievethe desired video sequence among
voluminous amounts of video data in an efficient and semantically
meaningful way. This book also presents a modeling framework and a
prototype of a content-based video management system that
integrates the three methods and provides efficient, flexible, and
scalable content-based video retrieval. The proposed approach is
validated in the domain of sport videos for which some experimental
results are presented.
Content-Based Video Retrieval: A Database Perspective is designed
for a professional audience, composed of researchers and
practitioners in industry. This book is also suitable as a
secondary text for graduate-level students in computer science and
electrical engineering.
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