Content based video: part 1

Published on 12/03,2016

In the following my previous post I want to talk about another aspect of indexing in this post which is content based video indexing.

Shot detection
In this operation, for the query clip and the target videos, we perform transitional shot detection to divide a video into a set of sequential shots. Finally, the key-frame of each shot is defined.Hence, a shot within a video clip is represented by a key-frame in the remainder of this paper.

Shot clustering and encoding

To construct the pattern-based index tree, encoding the shots is necessary. The main contribution of this work is that, the feature dimensionality can be reduced substantially and the pattern matching cost becomes very low. In this work, the shots are clus-tered by the well-known algorithm k-means and each shot is as-signed a symbol by its belonging cluster number.

Indexing stage

After the video clips in the database are symbolized,bellow tabel is a simple example of clip-transaction list that contains 4 target clips. Each clip consists of several sequential shot-patterns. By this clip-transaction list, we can build index-tree, with respect to FPI-tree.

the task for building the index-tree can be divided into two parts, including the generation of temporal patterns and the construction of index-tree.

I will talk about constructing index tree in the next post. 



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