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Author

Patrick Tresset

Other affiliations: University of London
Bio: Patrick Tresset is an academic researcher from Goldsmiths, University of London. The author has contributed to research in topics: Sketch & Autonomous agent. The author has an hindex of 5, co-authored 8 publications receiving 185 citations. Previous affiliations of Patrick Tresset include University of London.

Papers
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Journal ArticleDOI
TL;DR: This work presents here their first efforts in implementing two different versions of visual feedback to permit the robot to iteratively augment and improve a drawing which initially is built from a process of salient lines recovery, and presents the arguments in favour of such a position for the graphics community to reflect upon.

128 citations

Book Chapter
01 Oct 2005
TL;DR: In this paper, the problem of generating art with a computer system, as it relates to the understanding of a drawing style, was considered, and the goal was to mimic the process developed by the artist, rather than aiming at results exactly reproducing his way of drawing a portrait.
Abstract: We consider the problem of generating art with a computer system, as it relates to the understanding of a drawing style. Our system in its present development is able to sketch faces automatically, starting from a picture, typically a photographic snapshot of a scene with humans. Once a digital image is considered, the system automatically finds where some of the faces (or face-like patterns) are and isolate these. Each face image pattern is then used to produce a stylised portrait. The style which the system aims at using is derived from the one the first author has developed over the years in his artistic practice. The goal is for the final system to mimic the process developed by the artist, rather than aiming at results exactly reproducing his way of drawing a portrait. Nevertheless, the produced sketches are in the style of the artist. Various steps in the process of producing a sketch by the artist were isolated, including: image segmentation, filtering, shape selection and depiction, filling and shading. The implementation of these steps relies on an understanding of human visual perception, of the artist’s work process, and of advances made in computer vision.

27 citations

DOI
04 Jun 2012
TL;DR: Paul, a robotic installation that produces observational sketches of people is described, considered of interest by fine art professionals in recent art fairs and exhibitions, as well as by the public at large.
Abstract: In this paper we describe Paul, a robotic installation that produces observational sketches of people. The sketches produced have been considered of interest by fine art professionals in recent art fairs and exhibitions, as well as by the public at large. We identify factors that may account for the perceived qualities of the produced sketches. A technical overview of the system is also presented.

23 citations

01 Jan 2014
TL;DR: In this article, the authors present a conceptual framework that introduces the notion of style-space in relation to the visual arts and introduces the importance of intentionality and embodiment, two interrelated elements that are fundamental in the appreciation of visual artworks such as paintings and drawings.
Abstract: In this paper we report on our research into the develop- ment of computational embodied systems dedicated to the produc- tion of artworks. We present a conceptual framework that introduces the notion of style-space in relation to the visual arts. This frame- work underpins and guides our general approach to the development of autonomous agents capable of producing objects that have artistic value. In addition we introduce the importance of intentionality and embodiment, two interrelated elements that are fundamental in the appreciation of visual artworks such as paintings and drawings. Our practical research has at this stage only touched upon the develop- ment of agents that are adapted and sufficiently skilled to display the lowest level of artistic autonomy. Having such agents is essential to conduct further research into the autonomous invention of artistically valuable styles. Two of these skilled agents and their production are presented in this document.

17 citations

Proceedings ArticleDOI
30 Jul 2006
TL;DR: It is proposed that the modelled drawing process is the most spontaneous technique Tresset uses, not the most precise, which gives the most dramatic effects, and the aesthetic effect of the drawing, its mood, is due in large part to its apparent imprecision.
Abstract: 1 Concept We consider the problem of generating face sketches with a computer system, based on the understanding of a drawing style. Our research goal is for the system to mimic the interplay between the ensemble of processes — perceptual, cognitive, motor — active when a draughtsman is sketching. One hypothesis we are exploring is that the aesthetics of a sketch is dependent on each individual step involved in the collection of processes leading to the creation of a stylised portrait, as well as in the interactions between such processes. A second hypothesis we formulate is that during a sketch session each limitation, approximation, shortcut performed by the draughtsman due to his/her physical, perceptual, or cognitive impairments or qualities are what constitute the final mood, style, aesthetic of the sketch. Interestingly, the simulation of a stylised portrait sketching session via a computational model remains approximate, and as such the computerised system might be thought to draw in its own limited style. The modelled drawing process is the most spontaneous technique Tresset uses, not the most precise, which gives the most dramatic effects. The aesthetic effect of the drawing, its mood, is due in large part to its apparent imprecision.

6 citations


Cited by
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Journal ArticleDOI

728 citations

Proceedings Article
David Ha1, Douglas Eck1
11 Apr 2017
TL;DR: Sketch-rnn is presented, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects that is trained on thousands of crude human-drawn images representing hundreds of classes.
Abstract: We present sketch-rnn, a recurrent neural network (RNN) able to construct stroke-based drawings of common objects. The model is trained on thousands of crude human-drawn images representing hundreds of classes. We outline a framework for conditional and unconditional sketch generation, and describe new robust training methods for generating coherent sketch drawings in a vector format.

485 citations

Journal ArticleDOI
TL;DR: This paper presents a taxonomy of the 2D NPR algorithms developed over the past two decades, structured according to the design characteristics and behavior of each technique, and describes a chronology of development from the semiautomatic paint systems of the early nineties, through to the automated painterly rendering system of the late nineties driven by image gradient analysis.
Abstract: This paper surveys the field of nonphotorealistic rendering (NPR), focusing on techniques for transforming 2D input (images and video) into artistically stylized renderings. We first present a taxonomy of the 2D NPR algorithms developed over the past two decades, structured according to the design characteristics and behavior of each technique. We then describe a chronology of development from the semiautomatic paint systems of the early nineties, through to the automated painterly rendering systems of the late nineties driven by image gradient analysis. Two complementary trends in the NPR literature are then addressed, with reference to our taxonomy. First, the fusion of higher level computer vision and NPR, illustrating the trends toward scene analysis to drive artistic abstraction and diversity of style. Second, the evolution of local processing approaches toward edge-aware filtering for real-time stylization of images and video. The survey then concludes with a discussion of open challenges for 2D NPR identified in recent NPR symposia, including topics such as user and aesthetic evaluation.

249 citations

BookDOI
30 Oct 2012
TL;DR: This book focuses on image and video based NPR, where the input is a 2D photograph or a video rather than a 3D model, enabling both graduate students in computer graphics, computer vision or image processing and professional developers alike to quickly become familiar with contemporary techniques, enabling them to apply 2D NPR algorithms in their own projects.
Abstract: Non-photorealistic rendering (NPR) is a combination of computer graphics and computer vision that produces renderings in various artistic, expressive or stylized ways such as painting and drawing. This book focuses on image and video based NPR, where the input is a 2D photograph or a video rather than a 3D model. 2D NPR techniques have application in areas as diverse as consumer and professional digital photography and visual effects for TV and film production. The book covers the full range of the state of the art of NPR with every chapter authored by internationally renowned experts in the field, covering both classical and contemporary techniques. It will enable both graduate students in computer graphics, computer vision or image processing and professional developers alike to quickly become familiar with contemporary techniques, enabling them to apply 2D NPR algorithms in their own projects.

128 citations