Complex Visual Motion Analysis via Probabilistic Variational Methods
A Distributed and Collaborative Approach
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The explosive growth of the internet have accumulated gigantic amount of visual data. Management and retrieval of relevant information from it become a more and more difficult task. Moreover, as security becomes an important issue, there are numerous surveillance cameras all around the world which accumulate terabytes of video data every day. How to intelligently analyze these video data becomes a big challenge. These largely explain the boom of the research on complex motion analysis, the understanding of which would be essential for higher level tasks such as visual recognition and content u...
The explosive growth of the internet have
accumulated gigantic amount of visual data.
Management and retrieval of relevant information
from it become a more and more difficult task.
Moreover, as security becomes an important issue,
there are numerous surveillance cameras all around
the world which accumulate terabytes of video data
every day. How to intelligently analyze these video
data becomes a big challenge. These largely explain
the boom of the research on complex motion analysis,
the understanding of which would be essential for
higher level tasks such as visual recognition and
content understanding. This book provides a general
framework on complex motion analysis based on
probabilistic variational method. It provides a
distributed computational paradigm, since each
motion component is analyzed individually, with the
constraints from the other components being
reinforced. It is also a collaborative approach,
since it naturally integrates multiple information
cues to obtain the optimal solution.
accumulated gigantic amount of visual data.
Management and retrieval of relevant information
from it become a more and more difficult task.
Moreover, as security becomes an important issue,
there are numerous surveillance cameras all around
the world which accumulate terabytes of video data
every day. How to intelligently analyze these video
data becomes a big challenge. These largely explain
the boom of the research on complex motion analysis,
the understanding of which would be essential for
higher level tasks such as visual recognition and
content understanding. This book provides a general
framework on complex motion analysis based on
probabilistic variational method. It provides a
distributed computational paradigm, since each
motion component is analyzed individually, with the
constraints from the other components being
reinforced. It is also a collaborative approach,
since it naturally integrates multiple information
cues to obtain the optimal solution.
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