Skip to Main Content
Video content classification is an important element for efficient access and retrieval of video in any media content management system. Categorizing the video segments can help to provide convenience and ease in accessing the relevant video content without sequential scanning. In this paper, we present a Hidden Markov Model (HMM) based classification technique for sports videos. Speed of color changes is computed for each video frame and used as observation sequences in HMM for classification. Experiments using more than 1 hour of 18 training and 18 testing sports videos of 3 predefined genres (golf, hockey and football) give very satisfactory classification accuracy.