Painterly rendering techniques: A state-of-the-art review of current approaches

In this publication we will look at the different methods presented over the past few decades which attempt to recreate digital paintings. While previous surveys concentrate on the broader subject of non-photorealistic rendering, the focus of this paper is firmly placed on painterly rendering techniques. We compare different methods used to produce different output painting styles such as abstract, colour pencil, watercolour, oriental, oil and pastel. Whereas some methods demand a high level of interaction using a skilled artist, others require simple parameters provided by a user with little or no artistic experience. Many methods attempt to provide more automation with the use of varying forms of reference data. This reference data can range from still photographs, video, 3D polygonal meshes or even 3D point clouds. The techniques presented here endeavour to provide tools and styles that are not traditionally available to an artist. Copyright © 2012 John Wiley & Sons, Ltd

Stroke Based Painterly Rendering

International audienceMany traditional art forms are produced by an artist sequentially placing a set of marks, such as brush strokes, on a canvas. Stroke based Rendering (SBR) is inspired by this process, and underpins many early and contemporary Artistic Stylization algorithms. This Chapter outlines the origins of SBR, and describes key algorithms for placement of brush strokes to create painterly renderings from source images. The chapter explores both local greedy, and global optimization based approaches to stroke placement. The issue of creative control in SBR is also briefly discussed

Perception-based painterly rendering: funcionality and interface design

Painterly rendering (non-photorealistic rendering or NPR) aims at translating photographs into paintings with discrete brush strokes, simulating certain techniques (im- or expressionism) and media (oil or watercolour). Recently, our research into visual perception and models of processes in the visual cortex resulted in a new rendering scheme, in which detected lines and edges at different scales are translated into brush strokes of different sizes. In order to prepare a version which is suitable for many users, including children, the design of the interface in terms of window and menu system is very important. Discussions with artists and non-artists led to three design criteria: (1) the interface must reflect the procedures and possibilities that real painters follow and use, (2) it must be based on only one window, and (3) the menu system must be very simple, avoiding a jungle of menus and sub-menus. This paper explains the interface that has been developed

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

Stroke-Based Stylization Learning and Rendering with Inverse Reinforcement Learning

Among various traditional art forms, brush stroke drawing is one of the widely used styles in modern computer graphic tools such as GIMP, Photoshop and Painter. In this paper, we develop an AI-aided art authoring (A4) system of non- photorealistic rendering that allows users to automatically generate brush stroke paintings in a specific artist’s style. Within the reinforcement learning framework of brush stroke generation proposed by Xie et al.[Xie et al., 2012], our contribution in this paper is to learn artists’ drawing styles from video-captured stroke data by inverse reinforcement learning. Through experiments, we demonstrate that our system can successfully learn artists’ styles and render pictures with consistent and smooth brush strokes