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• W2147926254 abstract "In this paper we address the problem of dynamic trajectory segmentation for human-computer interfaces. We are concerned with locally linear trajectories. Trajectory points are obtained from a hand feature detector. First, a tensor voting technique is used to filter the trajectory and to construct a smooth trajectory from the sparse collection of detected points. The tensor voting scheme is also in accordance with perceptual principles. Local linearity of the trajectory permits us to have a decision based on an analysis of the corresponding modes in the Radon space. A mode detector in this space allows us to find the orientation of each trajectory segment. The entire trajectory is encoded by a sequence of directions, thus, allowing a large number of possible meaningful gestures to be defined in the HCI." @default.
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• W2147926254 date "2011-05-01" @default.
• W2147926254 modified "2023-09-24" @default.
• W2147926254 title "Dynamic hand gesture recognition for human-computer interactions" @default.
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• W2147926254 doi "https://doi.org/10.1109/saci.2011.5872993" @default.
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