Automatic Motion Capture Data Denoising via Filtered Local Subspace Affinity and Low Rank Approximation

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In this paper, we formulate the Motion capture (MoCap) data denoising problem as the concatenation of piecewise motion matrix recovery problem, in which the moving trajectories of each piecewise motion always share the similar subspace representation. To this end, we present an automatic MoCap data denoising approach based on the filtered local subspace affinity (LSA) and low rank approximation. The proposed approach does not need any physical information about the underling structure of MoCap data or require auxiliary data sets for the training priors. The experiments have shown the promising results.