The Study of Semantic Analysis in Video Using Hidden Markov Model

• Main Author: 張智堯
• Other Authors: 王元凱
• Format: Others
• Language: zh-TW
• Published: 2003
• Online Access: http://ndltd.ncl.edu.tw/handle/36802421639397171073

碩士 === 輔仁大學 === 電子工程學系 === 91 === Movie is a kind of complex video with rich content. The analysis of movie is more complicated than other types of videos like surveillance, sport games, and documentaries. In this paper, a statistical approach using hidden Markov model to classify movie scenes is proposed. Two important kinds of movie scenes, dialogue and fighting scenes, are classified. Color and motion features are extracted for each frame. Features of all frames within a scene are regarded as a time series of observations that are statistically modeled by Gaussian mixture ergodic hidden Markov model. Two movies with 41 dialogue scenes and 15 fighting scenes are experimented. The highest accuracy rate can achieve 80%.