An integrated intelligent home video management system was proposed in this paper. Five different types of multimedia representative features were computed as the basis of the home video management system. With the aid of some machine learning techniques, such as SVM, neural network, adaboost algorithm, and the K-means clustering algorithm, we develop six main applications based on this system. These applications include detection of abnormal camera operation, shot boundary detection, fast-pan detection, face shot identification, key-frame extraction, and variable length video abstraction. Our system can help inexpert digital camcorder users manage their home video effectively in a smart way.
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