ETD Collection

Permanent URI for this collectionhttps://wiredspace.wits.ac.za/handle/10539/104


Please note: Digitised content is made available at the best possible quality range, taking into consideration file size and the condition of the original item. These restrictions may sometimes affect the quality of the final published item. For queries regarding content of ETD collection please contact IR specialists by email : IR specialists or Tel : 011 717 4652 / 1954

Follow the link below for important information about Electronic Theses and Dissertations (ETD)

Library Guide about ETD

Browse

Filters

20211

Settings

Author: search.filters.author.Ramgovind, Bryce Jiran

Search Results

Now showing 1 - 1 of 1
  • No Thumbnail Available
    Item
    Neural style transfer for character motion synthesis
    (2021) Ramgovind, Bryce Jiran
    In the field of animation, three-dimensional characters are assigned skeletons, or character rigs, to sim ulate the naturalistic movements of their real-world counterparts. Animators manipulate the character rig to allow for smooth, naturalistic movement. This research proposes using a combination of deep learning techniques to learn the manifold of human character motion, trained on motion capture data. The motion manifold is represented by the latent space of the convolutional auto-encoder. This repre sentation is subsequently transferred to any given locomotion, providing a high-quality motion sequence with a different style. This research builds upon the recent work of neural style transfer for images, but transports it to a new domain of human character motion. A qualitative study has been conducted on a group of participants to determine the success of the framework’s ability in transferring style to a newly synthesised locomotion. Participants were able to recognise stylised aspects within the synthesised loco motions generated from the deep learning framework. An investigation into the relationship between the amount of style and content on the style transfer constraint is presented. Further, the effect of varying gaits on the style transfer process between actors running and walking in a normal and zombie style are investigated. One should view style and content as an inter-related concept. This research provides an in terval of acceptable amounts of style. After a point, the more style placed on the style transfer constraint does not yield major changes on the newly synthesised locomotion. The zombie stylise motion manifold took longer to transfer when the actor was running. This research demonstrates that style transfer for human locomotion is capable