Abstract

Video classi#cation and segmentation are fundamental steps for e#cient accessing, retrieving and browsing large amount of video data. Wehave developed a scene classi#cation scheme using a Hidden Markov Model #HMM#- based classi#er. By utilizing the temporal behaviors of di#erent scene classes, HMM classi#er can e#ectively classify video segments into one of the prede#ned scene classes. In this paper, we describe two approaches for joint video classi#cation and segmentation based on HMM, which works by searching for the most likely class transition path utilizing the dynamic programming technique. 1. INTRODUCTION Video classi#cation and segmentation are fundamental steps for e#cient accessing, retrieving and browsing large amount of video data. Recently, several research groups have developed algorithms to detect scene change by incorporating audio and visual information. Most of these works #1, 2, 3# are based on some prior scene models, #e.g. dialog, setting, etc.# and accomplish ...

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