Computational models for the analysis and synthesis of graffiti tag strokes

In this paper we describe a system aimed at the generation and analysis of graffiti tags. We argue that the dynamics of the movement involved in generating tags is in large part --- and at a higher degree with respect to many other visual art forms --- determinant of their stylistic quality. To capture this notion computationally, we rely on a biophysically plausible model of handwriting gestures (the Sigma Lognormal Model proposed by Réjean Plamondon et al.) that permits the generation of curves which are aesthetically and kinetically similar to the ones made by a human hand when writing. We build upon this model and extend it in order to facilitate the interactive construction and manipulation of digital tags. We then describe a method that reconstructs any planar curve or a sequence of planar points with a set of corresponding model parameters. By doing so, we seek to recover plausible velocity and temporal information for a static trace. We present a number of applications of our system: (i) the interactive design of curves that closely resemble the ones typically observed in graffiti art; (ii) the stylisation and beautification of input point sequences via curves that evoke a smooth and rapidly executed movement; (iii) the generation of multiple instances of a synthetic tag from a single example. This last application is a step in the direction of our longer term plan of realising a system which is capable of automatically generating convincing images in the graffiti style space.