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Efficient indexing and retrieving objects of interest from large-scale surveillance videos are a significant and challenging topic. In this study, the authors present an effective multiple deep features learning approach for object retrieval in surveillance videos. Based on the discriminative convolutional neural network (CNN), they can learn multiple deep features to comprehensively describe the...
The main issue of video copy detection is to estimate a constant spatial-temporal transformation in object level between the original video and the copies. In this paper, we propose a multi-level trajectory modeling approach for video copy detection. It includes a rich trajectory description and a robust trajectory-to-trajectory matching to preserve and explore the trajectory characteristics in both...
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