NodeBox

Thesis challenges

We are often approached by thesis students with no programming skills who wish to participate in the research group. We have many open questions that require no technical background but are important to pushing the state-of-the-art of the software we make, and the research we do.

Here are some of the domains in which you can help out:

Building blocks of vector artwork

Requirements: solid skills with Adobe Illustrator (or comparable), drawing skills and aesthetic eye.

Part of the developments in the NodeBox software involves the creation of a database of vector artwork. 

• Vector shapes are typically created from scratch for each assignment which is a time-consuming process (under a tight deadline). Moreover, many amateurs and professionals alike lack the skill to draw their own shapes and are therefore dependent upon premade clipart and dingbat fonts. The aesthetic quality of available clipart is often low and unprofessional (i.e. frivolous), or otherwise highly influenced by the personal “style” of the artist that created them. 
• “Why can’t I draw the thing I have in my head?” Clipart is usually limited to predictable categories (holiday, work, anniversary - sometimes useful to amateurs but rarely for professionals). There is no clipart for a rabbit with wings sipping tea. This is the most serious limitation to creativity: existing clipart can be reused, but not easily rearranged or recombined to fit your own creative purposes. 

On a vector component level, NodeBox currently only has ovals, rectangles and Bézier curves to work with. If more complex shapes are required, users will have to design them from scratch. Other graphics software applications like Processing or Adobe Illustrator have similar issues. So how can we help people create and combine vector shapes?

We want to develop a free library of professional vector shapes that can be recombined into new and
bigger shapes inside NodeBox. Starting out bottom-up with shapes like fingers, hands, arms, noses, eyes, wings, leaves, branches, flowers, houses, rooftops, cars, wheels, etc. we hand others the building blocks to create more complex shapes that fit a personal context. Not everyone knows how to draw, but everyone knows how to play with Lego. Playing with building blocks is fun, fast and creatively stimulating.

We want to store the set of shapes in a semantic network. The building blocks are interrelated with is-a, is- part-of, is-opposite-of, is-related-to rules with additional metadata to describe their appearance on a perceptual level (e.g. huge, furry, sad). This allows for powerful search capabilities and integration with AI-algorithms. If a machine not only has access to the shapes but also knows how they relate to each other, it can offer suggestions as to what bigger blocks might look like (e.g. evolutionary architecture). 

Composition grammar

More information to follow.

Trends | Fashion

How do trends emerge? Who decides this season's fashionable colors and patterns? Why were cars angular and matte in the past, and curvy-glossy in the future? Does a small group of top-level designers get up one day and say, "I'm bored with Hawaii shirts and epaulets, today we're drawing stretch pants and typographic shirts"? This would imply that a few famous people randomly do what they like, and then get copied by the rest of the world until a "new trend" is established by silent, mutual agreement.

• Are trends counter-movements that want to break with (or revive) the past?
• Are trends constantly evolving or are they circular in a historical sense?
• Are trends bound geographically (e.g. American vs. Asian)? Why?
  
• Do trends have a foundation in the social and cultural conditions of that time?
• If so, can we predict new fashion trends, given that we know the social and cultural conditions of this time - by looking at news facts for example?

We are interested in data offering an overview of historical trends in the usage of colors, patterns, shapes, together with data of the cultural situation of that time. We are looking for strong arguments that fashion is (or is not) a by-product of cultural evolution in general, and solid models for predicting new trends.

Evolution of graphic design

Requirements: an interest in graphic design, culture and evolution (biology, game theory, memetics).

How has graphic design evolved?
In well-established scientific terms (Boden, 1990), we discern between P-creativity and H-creativity.

• Psychological creativity refers to an idea that is novel to the agent that produces it.
  For example: imagine the joy of you as a graphic design student finding out that deep purple and bright yellow look really great together, thinking yourself an artistic genius for a while, and finally learning that the two colors are opposite on the color wheel and have been paired by others for centuries past. The purple-yellow color harmony was a personal "discovery".
• Historically creative ideas on the other hand are those that are novel to society at large.
  This includes the invention of the wheel, the theory of gravity, the computer mouse, and so on. Few ideas are H-creative.

Aside from being P- or H-creative, a great deal (perhaps all) of human innovation can be understood as a new way of combining existing ideas, rules or objects. We can distinguish this kind of combinatorial creativity from exploratory (exploring the edges of a conceptual space) and the rarer transformational creativity (expanding the conceptual space and the available rules).

As an illustration to these principles, consider the birth of the Belgium-based New Beat music in the late 80s. The New Beat genre in its entirety is assumed to have emerged from a party trick of playing EBM vinyl records at a slower 33rpm tempo than 45rpm (A Split Second's Flesh). This implies that a new genre wasn't necessarily created by a single person, but rather by a social consensus that this kind of recombination of old music was allowed, exciting and fun.

The same goes for Marcel Duchamp's Fountain (a combinatory technique of placing an object in an unfamiliar context) which led to conceptual art (a transformational shift in the arts).

We are interested in how these dynamics apply to the graphic design. What are the shapes, colors, composition rules that define each graphic design "style"? How did these styles shift (how did the ruleset expand or change) historically to create new styles? When does a style shift into a new style? Given this data, how can we infer totally new design styles?

Human Robot Experiment 

Requirements: love for logic games, philosophy and humor.

Assume that - in analogy to Searle's Chinese Room - we have a machine that mindlessly applies the rules of color theory, composition, photography, etc. by mimicking what human designers did in the past. Assume that it processes feedback suggestions literally. Would this machine produce high-quality "aesthetic" output? Would the thought experiment produce interesting output? Satisfactory output?

We are interested in learning if "good art" is more about the aesthetic qualities of the end result, or more about the personality of the creator. It is often assumed that presentation, enthusiasm, hype and personality of the creator (lecturer/politician/...) garners half of the interest for the product he/she is trying to sell.

What if the end result is merely a product of parroting what everyone else is suggesting? Theoretically, these "others" are peers (fellow students/teachers/...) skilled in the domain of interest.If they say, "you should make it yellow instead", you make it yellow instead. So, theoretically, the sum of all their opinions should lead to a satisfying end result... after all, they are skilled, you did what they told you to do, and you didn't try to sneak in any of your personal quirks that no one really cares about. Everyone is getting what they asked for. Or not?