Dynamic Graffiti Stylisation with Stochastic Optimal Control

Berio, Daniel; Leymarie, Frederic Fol and Calinon, Sylvain. 2017. 'Dynamic Graffiti Stylisation with Stochastic Optimal Control'. In: Proceedings of the 4th International Conference on Movement Computing (MOCO). London, United Kingdom 28-30 June 2017. [Conference or Workshop Item]

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Abstract or Description

We present a method for the interactive generation of stylised letters, curves and motion paths that are similar to the ones that can be observed in art forms such as graffiti and calligraphy. We define various stylisations of a letter form over a common geometrical structure, which is given by the spatial layout of a sparse sequence of targets. Different stylisations are then generated by optimising the trajectories of a dynamical system that tracks the target sequence. The evolution of the dynamical system is computed with a stochastic formulation of optimal control, in which each target is defined probabilistically as a multivariate Gaussian. The covariance of each Gaussian explicitly defines the variability as well as the curvilinear evolution of trajectory segments. Given this probabilistic formulation, the optimisation procedure results in a trajectory distribution rather than a single path. It is then possible to stochastically sample from the distribution an infinite number of dynamically and aesthetically consistent trajectories which mimic the variability that is typically observed in human drawing or writing. We further demonstrate how this system can be used together with a simple user interface in order to explore different stylisations of interactively or procedurally defined letters.

Item Type:

Conference or Workshop Item (Paper)

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February 2017Accepted
28 June 2017Published

Event Location:

London, United Kingdom

Date range:

28-30 June 2017

Item ID:


Date Deposited:

08 Aug 2017 09:40

Last Modified:

29 Apr 2020 16:28



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