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Goldsmiths - University of London

Generating Calligraphic Trajectories with Model Predictive Control

Berio, Daniel; Calinon, Sylvain and Leymarie, Frederic Fol. 2017. 'Generating Calligraphic Trajectories with Model Predictive Control'. In: Graphics Interface 2017. Edmonton, Canada 16 - 19 May, 2017. [Conference or Workshop Item] (In Press)

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Abstract or Description

We describe a methodology for the interactive definition of curves and motion paths using a stochastic formulation of optimal control. We demonstrate how the same optimization framework can be used in different ways to generate curves and traces that are geometrically and dynamically similar to the ones that can be seen in art forms such as calligraphy or graffiti art. The method provides a probabilistic description of trajectories that can be edited similarly to the control polygon typically used in the popular spline based methods. Furthermore, it also encapsulates movement kinematics, deformations and variability. The user is then provided with a simple interactive interface that can generate multiple movements and traces at once, by visually defining a distribution of trajectories rather than a single one. The input to our method is a sparse sequence of targets defined as multivariate Gaussians. The output is a dynamical system generating curves that are natural looking and reflect the kinematics of a movement, similar to that produced by human drawing or writing.

Item Type: Conference or Workshop Item (Paper)

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Departments, Centres and Research Units:

Computing

Dates:

DateEvent
23 December 2016Submitted
6 March 2017Accepted
17 May 2017Published

Event Location:

Edmonton, Canada

Date range:

16 - 19 May, 2017

Item ID:

20169

Date Deposited:

07 Apr 2017 10:10

Last Modified:

28 Sep 2017 16:32

URI: http://research.gold.ac.uk/id/eprint/20169

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