Video Manga: Generating Semantically Meaningful Video Summaries.


This paper presents methods for automatically
creating pictorial video summaries that resemble
comic books. The relative importance of
video segments is computed from their length
and novelty. Image and audio analysis is used
to automatically detect and emphasize meaningful
events. Based on this importance measure,
we choose relevant keyframes. Selected
keyframes are sized by importance, and then
efficiently packed into a pictorial summary.
We present a quantitative measure of how well
a summary captures the salient events in a
video, and show how it can be used to improve
our summaries. The result is a compact and
visually pleasing summary that captures
semantically important events, and is suitable
for printing or Web access. Such a summary
can be further enhanced by including text captions
derived from OCR or other methods. We
describe how the automatically generated summaries
are used to simplify access to a large
collection of videos.