Music Video Summarization
Edward Wijaya
Hendra Setiawan

Contents
Multimedia Mining
Multimedia Mining for Digital Library
Music Video Summarization
Conclusion

Multimedia Mining
Summarization cast as Content Mining Problem – different with typical data mining
 Multimedia Mining – Pattern Discovery

Multimedia Mining for Digital Library
Growing number of multimedia material in Digital Library catered by Content-based Retrieval
Good summary is good candidate to facilitate user’s relevant judgement
Good summary serve better indexing
Accelerate the information seeking process (HCI aspects in Digital Libraries) for multimedia materials.

Video Summarization
Strong visual-audio synchronization
Audio-centric
Visual-centric
Weak visual-audio synchronization
Summarize each track
Alignment process

Music Video Summarization
Weak synchronization
Audio part is the salient part
Goal :
Provides a natural and effective audio-visual content overview
Maximized the coverage for both audio and visual contents without having to sacrifice either of them
[Shao Xi, et.al. Automatically Generating Summaries for Musical Video, 2003]

Music Summarization
Problem : How to generate a concise and informative content that best summarize the original content
Challenge :
Featureless sequences of bytes (Feature Extraction is very important) →MPEG-7 standard
Need content understanding
Good candidate : Non-trivial repetitive pattern

Visual Summarization
Challenges :
Require overall understanding of the content
Problem :
Identify duplicates and redundancies in a video sequences (Easy)
Finding the summary that has minimum redundancy

Visual and Audio Alignment
Criteria :
Smooth and Natural summary
Maximize the coverage for both audio and visual content

Conclusion
Summarization as Content Mining problem
Multimedia Mining for Digital Library
Music Video Summarization