Texture and temporal variations in scenes, and peculiarities of MPEG compression algorithms result in very complex frame-size data sets for any long-duration variable bit rate (VBR) video. A major hurdle in capturing the statistical behavior of such a data trace can be removed by segmentation of all frames into an appropriate number of analytically characterizable classes. However, video-trace segmentation techniques, particularly those which also enable preserving periodicity of group of pictures (GOP) in the modeled data, are lacking in the literature. In this paper, we propose and evaluate few techniques for segmenting frame-size data sets in any long-duration video trace. The proposed techniques partition the group of pictures in a video into size-based groups called shot-classes. Frames in each shot-class have three data-sets
Uttam K. Sarkar, Subramanian Ramakrishnan, Dilip S