@inproceedings {1852, title = {Automatic Generation of Statistical Shape Models in Motion}, booktitle = {Advances in Human Factors in Simulation and Modeling (AHFE 2018)}, volume = {780}, year = {2019}, pages = {170{\textendash}178}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, 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.}, isbn = {978-3-319-94223-0}, doi = {10.1007/978-3-319-94223-0_16}, author = {Femke Danckaers and Scataglini, Sofia and Haelterman, Robby and Van Tiggelen, Damien and Toon Huysmans and Jan Sijbers}, editor = {Cassenti, Daniel N.} } @inproceedings {1873, title = {Moving Statistical Body Shape Models Using Blender}, booktitle = {Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018)}, year = {2019}, pages = {28{\textendash}38}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {In this paper, we present a new framework to integrate movement acquired by a motion capture system to a statistical body shape model using Blender. This provides a visualization of a digital human model based upon anthropometry and biomechanics of the subject. A moving statistical body shape model helps to visualize physical tasks with inter-individual variability in body shapes as well as anthropometric dimensions. This parametric modeling approach is useful for reliable prediction and simulation of the body shape movement of a specific population with a few given predictors such as stature, body mass index and age.}, isbn = {978-3-319-96077-7}, doi = {10.1007/978-3-319-96077-7_4}, author = {Scataglini, Sofia and Femke Danckaers and Haelterman, Robby and Toon Huysmans and Jan Sijbers}, editor = {Bagnara, Sebastiano and Tartaglia, Riccardo and Albolino, Sara and Alexander, Thomas and Fujita, Yushi} } @inproceedings {1874, title = {Using 3D Statistical Shape Models for Designing Smart Clothing}, booktitle = {Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018)}, year = {2019}, pages = {18{\textendash}27}, publisher = {Springer International Publishing}, organization = {Springer International Publishing}, address = {Cham}, abstract = {In this paper we present an innovative approach to design smart clothing using statistical body shape modeling (SBSM) from the CAESAR{\texttrademark} dataset. A combination of different digital technologies and applications are used to create a common co-design workflow for garment design. User and apparel product design and developers can get personalized prediction of cloth sizing, fitting and aesthetics.}, isbn = {978-3-319-96077-7}, doi = {10.1007/978-3-319-96077-7_3}, author = {Scataglini, Sofia and Femke Danckaers and Haelterman, Robby and Toon Huysmans and Jan Sijbers and Andreoni, Giuseppe}, editor = {Bagnara, Sebastiano and Tartaglia, Riccardo and Albolino, Sara and Alexander, Thomas and Fujita, Yushi} }