Vierailuluento Daniel Berio: "Procedural and computer aided design of graffiti art and calligraphy"
How can computing tools and robotics support graffiti art and calligraphy? Programmer and artist Daniel Berio presents and demonstrates the use of ”stroke primitives” as building blocks in his design and art.
In this talk I will present a series of methods aimed at the computer aided design of traditional graffiti art and calligraphy. The core of these methods is a set of "stroke primitives”, building blocks that can be combined to produce stylized designs, while giving a high level of parametric control to the user. These primitives mimic the process typically used to design graffiti letters and exploit well known principles of motor control to model the way in which an artist moves when incrementally tracing stylised letterforms. Along with some technical details, I will demonstrate different applications of this system ranging from the interactive and procedural design of stylized letterforms to the generation of smooth motion paths for computer animation or machine/robot drawing applications. To conclude, I will discuss how these tools feed into my work as an artist.
You can pop in without registering! If you wish to have a 1-to-1 meeting with Daniel in the afternoon on Monday 10 Oct, or on Tuesday 11 Oct, book your meeting through the link on the registration page.
The event will be recorded, but not streamed online.
Daniel Berio is a researcher, programmer and artist working between computer graphics, robotics and graffiti art. He recently completed a PhD in computing at Goldsmiths, University of London, where he researched methods for the computer aided design and procedural generation of (synthetic) graffiti art and calligraphy. Previously, Daniel specialized in multimedia software development, especially applications involving real-time hardware accelerated rendering and vector graphics techniques. Artistically, Daniel comes from a graffiti writing background and he explores this same aesthetic in algorithmically generated forms.