@InProceedings{BoehsVierPere:2018:DeExBo,
author = "Boehs, Gustavo Eggert and Viera, Milton Luiz Horn and Pereira,
Clovis Geyer",
affiliation = "{Universidade Federal de Santa Catarina} and {Universidade Federal
de Santa Catarina} and {Universidade Federal de Santa Catarina}",
title = "Decoupling Expressiveness and Body-Mechanics in Human Motion",
booktitle = "Proceedings...",
year = "2018",
editor = "Ross, Arun and Gastal, Eduardo S. L. and Jorge, Joaquim A. and
Queiroz, Ricardo L. de and Minetto, Rodrigo and Sarkar, Sudeep and
Papa, Jo{\~a}o Paulo and Oliveira, Manuel M. and Arbel{\'a}ez,
Pablo and Mery, Domingo and Oliveira, Maria Cristina Ferreira de
and Spina, Thiago Vallin and Mendes, Caroline Mazetto and Costa,
Henrique S{\'e}rgio Gutierrez and Mejail, Marta Estela and Geus,
Klaus de and Scheer, Sergio",
organization = "Conference on Graphics, Patterns and Images, 31. (SIBGRAPI)",
publisher = "IEEE Computer Society",
address = "Los Alamitos",
keywords = "motion capture, deep learning, animation.",
abstract = "Modern motion capturing systems can accurately store human motion
with high precision. Editing this kind of data is troublesome, due
to the amount and complexity of data. In this paper, we present a
method for decoupling the aspects of human motion that are
strictly related to locomotion and balance, from other movements
that may convey expressiveness and intentionality. We then
demonstrate how this decoupling can be useful in creating
variations of the original motion, or in mixing different actions
together.",
conference-location = "Foz do Igua{\c{c}}u, PR, Brazil",
conference-year = "29 Oct.-1 Nov. 2018",
doi = "10.1109/SIBGRAPI.2018.00035",
url = "http://dx.doi.org/10.1109/SIBGRAPI.2018.00035",
language = "en",
ibi = "8JMKD3MGPAW/3RMTUPH",
url = "http://urlib.net/ibi/8JMKD3MGPAW/3RMTUPH",
targetfile = "decoupling.pdf",
urlaccessdate = "2024, Apr. 30"
}