Learning part-based models for animation from surface motion capture

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Abstract

Surface motion capture (Surf Cap) enables 3D reconstruction of human performance with detailed cloth and hair deformation. However, there is a lack of tools that allow flexible editing of Surf Cap sequences. In this paper, we present a Laplacian editing technique that constrains the mesh deformation to plausible surface shapes learnt from a set of examples. A part-Based representation of the mesh enables learning of surface deformation locally in the space of Laplacian coordinates, avoiding correlations between body parts while preserving surface details. This extends the range of animation with natural surface deformation beyond the whole-body poses present in the Surf Cap data. We illustrate successful use of our tool on three different characters. © 2013 IEEE.

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Tejera, M., & Hilton, A. (2013). Learning part-based models for animation from surface motion capture. In Proceedings - 2013 International Conference on 3D Vision, 3DV 2013 (pp. 159–166). https://doi.org/10.1109/3DV.2013.29

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