Fourier principles for emotion-based human figure animation
SIGGRAPH '95 Proceedings of the 22nd annual conference on Computer graphics and interactive techniques
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Verbs and Adverbs: Multidimensional Motion Interpolation
IEEE Computer Graphics and Applications
Style-based inverse kinematics
ACM SIGGRAPH 2004 Papers
Interactive low-dimensional human motion synthesis by combining motion models and PIK
Computer Animation and Virtual Worlds - CASA 2007
Social interactive human video synthesis
ACCV'10 Proceedings of the 10th Asian conference on Computer vision - Volume Part I
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The main focus of this paper is to present a method of reusing motion captured data by learning a generative model of motion. The model allows synthesis and blending of cyclic motion, whilst providing it with the style and realism present in the original data. This is achieved by projecting the data into a lower dimensional space and learning a multivariate probability distribution of the motion sequences. Functioning as a generative model, the probability density estimation is used to produce novel motions from the model and gradient based optimisation used to generate the final animation. Results show plausible motion generation and lifelike blends between different actions.