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• W2058431310 abstract "In this paper, we propose a temporal super resolution approach for quasi-periodic image sequence such as human gait. The proposed method effectively combines example-based and reconstruction-based temporal super resolution approaches. A periodic image sequence is expressed as a manifold parameterized by a phase and a standard manifold is learned from multiple high frame-rate sequences in the training stage. In the test stage, an initial phase for each frame of an input low frame-rate image sequence is estimated based on the standard manifold at first, and the manifold reconstruction and the phase estimation are then iterated to generate better high frame-rate images in the energy minimization framework that ensures the fitness to both the input images and the standard manifold. The proposed method is applied to low frame-rate gait recognition and experiments with real data of 100 subjects demonstrate a significant improvement by the proposed method, particularly for quite low frame-rate videos (e.g., 1 fps)." @default.
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• W2058431310 date "2012-06-01" @default.
• W2058431310 modified "2023-09-27" @default.
• W2058431310 title "Video from nearly still: An application to low frame-rate gait recognition" @default.
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• W2058431310 doi "https://doi.org/10.1109/cvpr.2012.6247844" @default.
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