Abstract
Statistical body shape modeling (SBSM) is a well-known technique to map out the variability of body shapes and is commonly used in 3D anthropometric analyses. In this paper, a new approach to integrate movement acquired by a motion capture system with a body shape is proposed. This was done by selecting landmarks on a body shape model, and predicting a body shape based on features. Then, a virtual skeleton was generated relative to those landmarks. This skeleton was parented to a body shape, allowing to modify its pose and to add pre-recorded motion to different body shapes in a realistic way.
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Acknowledgements
This work was supported by the Agency for Innovation by Science and Technology in Flanders (IWT-SB 141520).
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Danckaers, F., Scataglini, S., Haelterman, R., Van Tiggelen, D., Huysmans, T., Sijbers, J. (2019). Automatic Generation of Statistical Shape Models in Motion. In: Cassenti, D. (eds) Advances in Human Factors in Simulation and Modeling. AHFE 2018. Advances in Intelligent Systems and Computing, vol 780. Springer, Cham. https://doi.org/10.1007/978-3-319-94223-0_16
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DOI: https://doi.org/10.1007/978-3-319-94223-0_16
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