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• W2199731258 abstract "This report considers the problem of using marker locations from optical motion capture data to identify and parameterise the underlying human skeleton structure and motion over time. It is concerned with real-time algorithms suitable for use within a visual feedback system. The algorithms presented require 3 markers on each limb segment and can be implemented in a sequential fashion; hence the computational cost of updating the centres of rotation is independent of the number of data points previously available. However, a common problem in motion capture is marker occlusion. Most current methods are only useful for offline processing or become ineffective when a significant proportion of markers are missing for a long period of time. This report presents an integrated framework which predicts the occluded marker positions using a Kalman filter in combination with inferred information from neighbouring markers and thereby maintains a continuous data-flow. The results are accurate and reliable even in cases where all markers on a limb segment are occluded, or one or two markers are non-visible for a large sequence of frames. Moreover, it investigates several extensions of the proposed methodology for real-time applications using a sophisticated variable turn model, together with rotor prediction and unscented theory for filtering. It compares each individual method according to its accuracy, complexity and processing time and suggests the optimal solution for each case. Pre-defined models are not required and skeleton fitting to this complete data can then be updated in real-time." @default.
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• W2199731258 date "2008-09-16" @default.
• W2199731258 modified "2023-09-23" @default.
• W2199731258 title "Methods for real-time restoration and estimation in optical motion capture" @default.
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