Character Animation Reconstruction from Content-Based Motion Retrieval.

Wu, M. and Xiao, Z., 2018. Character Animation Reconstruction from Content-Based Motion Retrieval. In: Computer Graphics & Visual Computing (CGVC) 2018, 13th - 14th September 2018. (Submitted)

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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 (Paper)
Uncontrolled Keywords:Machine Learning ; Neural Network
Group:Faculty of Media & Communication
ID Code:31128
Deposited By: Unnamed user with email symplectic@symplectic
Deposited On:14 Aug 2018 15:51
Last Modified:15 Sep 2018 01:08


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