Abstract
In this paper, we describe a framework of analyzing programs belonging to different TV program genres Hidden Markov Models and pseudo-semantic feature s derived from video shots. Clustering using Gaussian mixture models is used to determine the order of the modes. Results for initial genre classification experiments using two simple features derived from video shots are given.