Semantic Video Object Segmentation for Content-Based Multimedia
Applications provides a thorough review of state-of-the-art
techniques as well as describing several novel ideas and algorithms
for semantic object extraction from image sequences. Semantic
object extraction is an essential element in content-based
multimedia services, such as the newly developed MPEG4 and MPEG7
standards. An interactive system called SIVOG (Smart Interactive
Video Object Generation) is presented, which converts user's
semantic input into a form that can be conveniently integrated with
low-level video processing. Thus, high-level semantic information
and low-level video features are integrated seamlessly into a smart
segmentation system. A region and temporal adaptive algorithm was
further proposed to improve the efficiency of the SIVOG system so
that it is feasible to achieve nearly real-time video object
segmentation with robust and accurate performances. Also included
is an examination of the shape coding problem and the object
segmentation problem simultaneously. Semantic Video Object
Segmentation for Content-Based Multimedia Applications will be of
great interest to research scientists and graduate-level students
working in the area of content-based multimedia representation and
applications and its related fields.
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