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.