Due to the rapid growth of mass storage technologies,
people may save large amounts of multimedia contents,
but may not have sufficient time to view them all.
They may want the displayer automatically filtering
out insignificant parts but showing only the
remarkable segments. Conventional highlight
extraction techniques adopt rule-based approaches
that need lots of human efforts to analyze the video
sequences for a particular type of sports. This book
presents a generalized method that can be applied to
various types of sports videos. The Artificial Neural
Network (ANN) is utilized to extract highlights
without predefining rules of the highlight events.
The framework should help researchers and design
engineers in industry implement efficient highlight
browsing system on real-time embedded systems and
applications, such as PVR and portable DVD.
people may save large amounts of multimedia contents,
but may not have sufficient time to view them all.
They may want the displayer automatically filtering
out insignificant parts but showing only the
remarkable segments. Conventional highlight
extraction techniques adopt rule-based approaches
that need lots of human efforts to analyze the video
sequences for a particular type of sports. This book
presents a generalized method that can be applied to
various types of sports videos. The Artificial Neural
Network (ANN) is utilized to extract highlights
without predefining rules of the highlight events.
The framework should help researchers and design
engineers in industry implement efficient highlight
browsing system on real-time embedded systems and
applications, such as PVR and portable DVD.