[{"key":"dc.contributor.author","value":"Xinyi , Zhang","language":null},{"key":"dc.date.accessioned","value":"2018-08-23T15:47:20Z","language":null},{"key":"dc.date.available","value":"2018-08-23T15:47:20Z","language":"*"},{"key":"dc.date.issued","value":"2018","language":"en"},{"key":"dc.identifier.uri","value":"http:\/\/hdl.handle.net\/2429\/66905","language":null},{"key":"dc.description.abstract","value":"Keyframing is the main method used by animators to choreograph appealing motions,\r\nbut the process is tedious and labor-intensive. In this thesis, we present a\r\ndata-driven autocompletion method for synthesizing animated motions from input\r\nkeyframes. Our model uses an autoregressive two-layer recurrent neural network\r\nthat is conditioned on target keyframes. Given a set of desired keys, the trained\r\nmodel is capable of generating a interpolating motion sequence that follows the\r\nstyle of the examples observed in the training corpus.\r\nWe apply our approach to the task of animating a hopping lamp character and\r\nproduce a rich and varied set of novel hopping motions using a diverse set of hops\r\nfrom a physics-based model as training data. We discuss the strengths and weaknesses\r\nof this type of approach in some detail.","language":"en"},{"key":"dc.language.iso","value":"eng","language":"en"},{"key":"dc.publisher","value":"University of British Columbia","language":"en"},{"key":"dc.rights","value":"Attribution-NonCommercial-NoDerivatives 4.0 International","language":"*"},{"key":"dc.rights.uri","value":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/","language":"*"},{"key":"dc.title","value":"Data driven auto-completion for keyframe animation","language":"en"},{"key":"dc.type","value":"Text","language":"en"},{"key":"dc.degree.name","value":"Master of Science - MSc","language":"en"},{"key":"dc.degree.discipline","value":"Computer Science","language":"en"},{"key":"dc.degree.grantor","value":"University of British Columbia","language":"en"},{"key":"dc.date.graduation","value":"2018-09","language":"en"},{"key":"dc.type.text","value":"Thesis\/Dissertation","language":"en"},{"key":"dc.description.affiliation","value":"Science, Faculty of","language":"en"},{"key":"dc.description.affiliation","value":"Computer Science, Department of","language":"en"},{"key":"dc.degree.campus","value":"UBCV","language":"en"},{"key":"dc.description.scholarlevel","value":"Graduate","language":"en"},{"key":"atmire.cua.enabled","value":"","language":""}]