Wu, M. and Xiao, Z., 2018. Character animation reconstruction from content based motion retrieval. In: Computer Graphics & Visual Computing (CGVC) 2018, 13 - 14 September 2018, Swansea, UK.
Full text available as:
|
PDF
Character_Animation_Reconstruction.pdf - Accepted Version Available under License Creative Commons Attribution Non-commercial No Derivatives. 173kB | |
Copyright to original material in this document is with the original owner(s). Access to this content through BURO is granted on condition that you use it only for research, scholarly or other non-commercial purposes. If you wish to use it for any other purposes, you must contact BU via BURO@bournemouth.ac.uk. Any third party copyright material in this document remains the property of its respective owner(s). BU grants no licence for further use of that third party material. |
Official URL: http://www.eguk.org.uk/CGVC2018/
Abstract
We present the initial design of a motion reconstruction framework for character animation which encompasses the use of supervised and unsupervised learning techniques for the retrieval and synthesis of new realistic motion. Taking advantage of the large amounts of Motion Capture data accumulated over the years, our aim is to shorten animation production times by providing animators with more control over the specification of high-level parameters and a user-friendly way of retrieving and reusing this data, applying clustering to organize the human motion database and Neural Networks for motion generation
Item Type: | Conference or Workshop Item (Poster) |
---|---|
Uncontrolled Keywords: | Motion Capture; Machine learning; Motion processing |
Group: | Faculty of Media & Communication |
ID Code: | 31144 |
Deposited By: | Symplectic RT2 |
Deposited On: | 22 Aug 2018 14:08 |
Last Modified: | 14 Mar 2022 14:12 |
Downloads
Downloads per month over past year
Repository Staff Only - |