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

The Utility of Beautiful Visualizations

Geovisualizations provide a means to inspect large complex multivariate datasets for information that would not otherwise be available with a tabular view or summary statistics alone. Aesthetically appealing visualizations can elicit prolonged exploration and encourage discovery. Creating data geovisualizations that are effective and beautiful is an important yet difficult challenge. Here we present a tool for rendering geovisualizations of continuous spatial data using the painterly techniques of impressionist-era artists. The techniques, which have been tested in controlled studies, vary the visual properties (e.g., hue, size, and tilt) of brush strokes to represent multiple data attributes simultaneously in each location. To demonstrate this technique, we render two examples 1) weather data attributes (e.g., temperature, windspeed, atmospheric pressure) from the NOAA Global Forecast System and 2) fragile state indices as assessed by Foreign Policy Magazine. These examples demonstrate how open source geospatial visualizations can harness aesthetics to enhance visual communication and viewer engagement

Automatic painting with economized strokes

Journal ArticleWe present a method that takes a raster image as input and produces a painting-like image composed of strokes rather than pixels. Unlike previous automatic painting methods, we attempt to use very few brush-strokes. This is accomplished by first segmenting the image into features, finding the medial axes points of these features, converting the medial axes points into ordered lists of image tokens, and finally rendering these lists as brush strokes. Our process creates images reminiscent of modern realist painters who often want an abstract or sketchy quality in their work

Artistic vision: painterly rendering using computer vision techniques

Journal ArticleWe present a method that takes a raster image as input and produces a painting-like image composed of strokes rather than pixels. Unlike previous automatic painting methods, we attempt to keep the number of brush-stroke small. This is accomplished by first segmenting the image into features, finding the medial axes points of these features, converting the medial axes points into ordered lists of image tokens, and finally rendering these lists as brush strokes. Our process creates images reminiscent of modern realist painters who often want an abstract or sketchy quality in their work

Processing images and video for an impressionist effect

This paper describes a technique that transforms ordinary video segments into animations that have a hand-painted look. Our method is the first to exploit temporal coherence in video clips to design an automatic filter with a hand-drawn animation quality, in this case, one that produces an Impressionist effect. Off-the-shelf image processing and rendering techniques are employed, modified and combined in a novel way. This paper proceeds through the process step by step, providing helpful hints for tuning the off-the-shelf parts as well as describing the new techniques and bookkeeping used to glue the parts together. 1

Image preprocessing for artistic robotic painting

Artistic robotic painting implies creating a picture on canvas according to a brushstroke map preliminarily computed from a source image. To make the painting look closer to the human artwork, the source image should be preprocessed to render the effects usually created by artists. In this paper, we consider three preprocessing effects: aerial perspective, gamut compression and brushstroke coherence. We propose an algorithm for aerial perspective amplification based on principles of light scattering using a depth map, an algorithm for gamut compression using nonlinear hue transformation and an algorithm for image gradient filtering for obtaining a well-coherent brushstroke map with a reduced number of brushstrokes, required for practical robotic painting. The described algorithms allow interactive image correction and make the final rendering look closer to a manually painted artwork. To illustrate our proposals, we render several test images on a computer and paint a monochromatic image on canvas with a painting robot

Higher level techniques for the artistic rendering of images and video

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