The amount of audiovisual information available in digital format has
grown exponentially in recent years. Gigabytes of new images, audio and
video clips are generated and stored everyday. Most audiovisual content
can be accessed through the Internet, which is a very large,
unstructured, distributed information database. Searching and retrieving
multimedia information from the Web has been limited to the use of
keywords.
Over the past decade, many researchers, mostly from the Image Processing
and Computer Vision community, have started to investigate possible ways
of retrieving visual information based solely on its contents. Instead
of being manually annotated using keywords, images and video clips would
be indexed by their own visual content, such as color, texture, objects'
shape and movement, among others. Research in the field of content-based
image and video retrieval (CBIVR) is very active. Many research groups
in leading universities, research institutes, and companies are actively
working in this field. Their ultimate goal is to enable users to
retrieve the desired image or video clip among massive amounts of visual
data in a fast, efficient, semantically meaningful, friendly, and
location-independent manner. Applications of CBIVR systems include
digital libraries, video-on-demand systems, geographic information
systems, astronomical research, satellite observation systems, and
criminal investigation systems, among many others.
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.
Content-Based Image And Video Retrieval is designed to meet the
needs of a professional audience composed of researchers, and
practitioners in industry and graduate-level students in Computer
Science and Engineering.
