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Continuous action recognition in video is more complicated compared with traditional isolated action recognition. Besides the high variability of postures and appearances of each action, the complex temporal dynamics of continuous action makes this problem challenging. In this study, the authors propose a hierarchical framework combining convolutional neural network (CNN) and hidden Markov model (HMM),...
In recent years, enlightened by data mining, more and more researchers over the world show great interests in video mining, which deals with the extraction of semantic info, implicit patterns and knowledge from video data to enhance the smart level of video applications. This paper investigates video mining technologies. The concepts, technical approaches and applications of video mining are summarized...
To discover similar video segments from surveillance video sequence, a new approach is proposed for clustering motion data of moving objects. A simple background subtraction algorithm is used to get the binary mask of moving objects for segmenting the video sequence captured by fixed camera. Then a mixture of hidden Markov models (HMMs) using the expectation-maximization (EM) scheme is fitted to the...
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