Exploring a Parameterized Portrait Painting Space

We overview our interdisciplinary work building parameterized knowledge domains and their authoring tools that allow for expression systems which move through a space of painterly portraiture. With new computational systems it is possible to conceptually dance, compose and paint in higher level conceptual spaces. We are interested in building art systems that support exploring these spaces and in particular report on our software-based artistic toolkit and resulting experiments using parameter spaces in face based new media portraiture. This system allows us to parameterize the open cognitive and vision-based methodology that human artists have intuitively evolved over centuries into a domain toolkit to explore aesthetic realizations and interdisciplinary questions about the act of portrait painting as well as the general creative process. These experiments and questions can be explored by traditional and new media artists, art historians, cognitive scientists and other scholars

Incorporating characteristics of human creativity into an evolutionary art algorithm

A perceived limitation of evolutionary art and design algorithms is that they rely on human intervention; the artist selects the most aesthetically pleasing variants of one generation to produce the next. This paper discusses how computer generated art and design can become more creatively human-like with respect to both process and outcome. As an example of a step in this direction, we present an algorithm that overcomes the above limitation by employing an automatic fitness function. The goal is to evolve abstract portraits of Darwin, using our 2nd generation fitness function which rewards genomes that not just produce a likeness of Darwin but exhibit certain strategies characteristic of human artists. We note that in human creativity, change is less choosing amongst randomly generated variants and more capitalizing on the associative structure of a conceptual network to hone in on a vision. We discuss how to achieve this fluidity algorithmically

Rembrandt\u27s Textural Agency: A Shared Perspective in Visual Art and Science

This interdisciplinary paper hypothesizes that Rembrandt developed new painterly techniques — novel to the early modern period — in order to engage and direct the gaze of the observer. Though these methods were not based on scientific evidence at the time, we show that they nonetheless are consistent with a contemporary understanding of human vision. Here we propose that artists in the late ‘early modern’ period developed the technique of textural agency — involving selective variation in image detail — to guide the observer’s eye and thereby influence the viewing experience. The paper begins by establishing the well-known use of textural agency among modern portrait artists, before considering the possibility that Rembrandt developed these techniques in his late portraits in reaction to his Italian contemporaries. A final section brings the argument full circle, with the presentation of laboratory evidence that Rembrandt’s techniques indeed guide the modern viewer’s eye in the way we propose

Incorporating characteristics of human creativity into an evolutionary art algorithm (journal article)

A perceived limitation of evolutionary art and design algorithms is that they rely on human intervention; the artist selects the most aesthetically pleasing variants of one generation to produce the next. This paper discusses how computer generated art and design can become more creatively human-like with respect to both process and outcome. As an example of a step in this direction, we present an algorithm that overcomes the above limitation by employing an automatic fitness function. The goal is to evolve abstract portraits of Darwin, using our 2nd generation fitness function which rewards genomes that not just produce a likeness of Darwin but exhibit certain strategies characteristic of human artists. We note that in human creativity, change is less choosing amongst randomly generated variants and more capitalizing on the associative structure of a conceptual network to hone in on a vision. We discuss how to achieve this fluidity algorithmically

Knowledge based approach to modeling portrait painting methodology

Traditional portrait artists use a specific but open human vision methodology to create a painterly portrait of a live or photographed sitter. Portrait artists attempt to simplify, compose and leave out what is irrelevant, emphasizing what is important. While seemingly a qualitative pursuit, artists use known but open techniques such as relying on source tone over colour to indirect into a colour temperature model, using "sharpness" to create a centre of interest, using edges to move the viewers gaze, and other techniques to filter and emphasize. Our interdisciplinary work attempts to compile and incorporate this portrait painter knowledge into a multi-space parameterized system that can create an array of painterly rendering output

Computationally rendered painterly portrait spaces

This work is ongoing output from research work by Steve DiPaola that attempts to build a computational painting system (called ‘painterly’) that allows aspects of art (the creative human act of fine art painting) and science (cognition, vision and perception; as well as computational design) to both enhance and validate each other. The research takes a novel approach to non photorealistic rendering (NPR) which relies on parameterizing a semantic knowledge space of how a human painter paints, that is, the creative and cognitive process

Shading with Painterly Filtered Layers: A Process to Obtain Painterly Portraits

In this thesis, I study how color data from different styles of paintings can be extracted from photography with the end result maintaining the artistic integrity of the art style and having the look and feel of skin. My inspiration for this work came from the impasto style portraitures of painters such as Rembrandt and Greg Cartmell. I analyzed and studied the important visual characteristics of both Rembrandt’s and Cartmell’s styles of painting.These include how the artist develops shadow and shading, creates the illusion of subsurface scattering, and applies color to the canvas, which will be used as references to help develop the final renders in computer graphics. I also examined how color information can be extracted from portrait photography in order to gather accurate dark, medium, and light skin shades. Based on this analysis, I have developed a process for creating portrait paintings from 3D facial models. My process consists of four stages: (1) Modeling a 3D portrait of the subject, (2) data collection by photographing the subjects, (3) Barycentric shader development using photographs, and (4) Compositing with filtered layers. My contributions has been in stages (3) and (4) as follows: Development of an impasto-style Barycentric shader by extracting color information from gathered photographic images. This shader can result in realistic looking skin rendering. Development of a compositing technique that involves filtering layers of images that correspond to different effects such as diffuse, specular and ambient. To demonstrate proof-of-concept, I have created a few animations of the impasto style portrait painting for a single subject. For these animations, I have also sculpted high polygon count 3D model of the torso and head of my subject. Using my shading and compositing techniques, I have created rigid body animations that demonstrate the power of my techniques to obtain impasto style portraiture during animation under different lighting conditions

Postures

In our present image-laden environment that only seems to keep growing, the nature of how we see and interpret this visual information becomes highly relevant for me in my art. Spectacle, nostalgia, notions of portraiture, theatricality and other visual reflections of our present culture industry, are all elements that I address in my work. It is with these ideas in mind that I construct visual fields where disparate forms and images coexist, forming new narratives aside from their individual isolated implications; incorporating art production methods that construct an evolving dichotomy that contains a sense of play, tension, and irony while evoking references to our current social experiences. Keywords: spectacle, nostalgia, portraiture, collective consciousness, culture industr

New Readings

This thesis explores the search for a creative process for my photographic studies over the past two years at Rochester Institute of Technology. It explains the thought behind the artwork such as why I am interested in the genre of still life, inspiration, process, and my future artistic goals. The subject matter of my thesis exhibition motivated me to explore the world of still life. By painting on an object, my imagery has evolved into a new reading that led to a new interpretation of the still life both physically and psychologically. My thesis images emphasize a new aesthetic experience not usually associated with traditional still life photography. In my graduate studies, I have come to know that I need the freedom to explore and to risk failure