@inproceedings{151ba4dfda9745b693d1e390fa3f1f5f,
title = "Automatic Generation of Statistical Shape Models in Motion",
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.",
keywords = "Statistical body shape model , Motion capturing , Shape prediction",
author = "Femke Danckaers and Sofia Scataglini and Robby Haelterman and {Van Tiggelen}, Damien and Toon Huysmans and Jan Sijbers",
year = "2019",
doi = "10.1007/978-3-319-94223-0_16",
language = "English",
isbn = "978-3-319-94222-3",
series = "Advances in Intelligent Systems and Computing ",
publisher = "Springer",
pages = "170--178",
editor = "Cassenti, {Daniel N.}",
booktitle = "Advances in Human Factors in Simulation and Modeling",
note = "AHFE 2018 : International Conferences on Human Factors and Simulation and Digital Human Modeling and Applied Optimization ; Conference date: 21-07-2018 Through 25-07-2018",
}