Frame difference normalization: an approach to reduce error rates of cut detection algorithms for MPEG videos

The segmentation of video sequences into shots is the first step towards video content analysis. Two kinds of shot boundaries can be distinguished: abrupt scene changes ("cuts") and gradual transitions. In this paper, we present a technique to reduce the error rates of cut detection algorithms based on pixel-wise or histogram-based frame difference metrics when operating directly on compressed MPEG video data. The proposed approach, called "frame difference normalization" (FDN), intends to eliminate the effects of a specific frame pattern in MPEG streams responsible for causing such errors. Experimental results will be presented to demonstrate the benefits of our proposal and its superiority over a more general noise filter. Furthermore, the proposed method is not limited to a particular algorithm but it is applicable to an entire class of cut detection algorithms.