Stochastic search algorithms for optimal content-based sampling of video sequences

Abstract

A video content representation framework is proposed in this paper, for extracting limited, but meaningful, information of video data, directly from the MPEG compressed domain. In particular, extraction of several representative shots is performed for each video sequence in a content based rate sampling framework. An approach, based on minimization of a cross-correlation criterion of the video frames has been adopted for the shot selection. For efficient implementation of the latter approach, a logarithmic search in a stochastic framework is proposed. The method always converges to the global minimum as is proven in the paper.