5,083 research outputs found
Modelling of content-aware indicators for effective determination of shot boundaries in compressed MPEG videos
In this paper, a content-aware approach is proposed to design multiple test conditions for shot cut detection, which are organized into a multiple phase decision tree for abrupt cut detection and a finite state machine for dissolve detection. In comparison with existing approaches, our algorithm is characterized with two categories of content difference indicators and testing. While the first category indicates the content changes that are directly used for shot cut detection, the second category indicates the contexts under which the content change occurs. As a result, indications of frame differences are tested with context awareness to make the detection of shot cuts adaptive to both content and context changes. Evaluations announced by TRECVID 2007 indicate that our proposed algorithm achieved comparable performance to those using machine learning approaches, yet using a simpler feature set and straightforward design strategies. This has validated the effectiveness of modelling of content-aware indicators for decision making, which also provides a good alternative to conventional approaches in this topic
More Efficient Algorithms and Analyses for Unequal Letter Cost Prefix-Free Coding
There is a large literature devoted to the problem of finding an optimal
(min-cost) prefix-free code with an unequal letter-cost encoding alphabet of
size. While there is no known polynomial time algorithm for solving it
optimally there are many good heuristics that all provide additive errors to
optimal. The additive error in these algorithms usually depends linearly upon
the largest encoding letter size.
This paper was motivated by the problem of finding optimal codes when the
encoding alphabet is infinite. Because the largest letter cost is infinite, the
previous analyses could give infinite error bounds. We provide a new algorithm
that works with infinite encoding alphabets. When restricted to the finite
alphabet case, our algorithm often provides better error bounds than the best
previous ones known.Comment: 29 pages;9 figures
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