Computer-generated watercolor

Curtis, Cassidy; Anderson, Spenser; Seims, Joshua; Fleischer, Kurt; Salesin, David

doi:10.1145/258734.258896

Cited by 368 publications

(263 citation statements)

References 40 publications

(42 reference statements)

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“…The results of the proposed method was first reported in our previous paper [13]. The method presented by Curtis et al [3] deals with only the properties of watercolor medium and does not consider the painting techniques which artists use when creating watercolor paintings. Furthermore, this method has high computational cost.…”

Section: Related Workmentioning

confidence: 98%

“…Considering these points, Curtis et al [3] proposed a watercolor painting method using fluid simulation of watercolor pigment in water. Their method creates beautiful images, but takes a long computation time.…”

Section: Related Workmentioning

confidence: 99%

“…These effects are fully exploited by artists to create impressive paintings. These pigment-based features are well categorized by Curtis et al [3] and they simulated these effects using fluid simulation and the Kubelka-Munk color model [15]. Although their approach well captured the various watercolor effects, their method is very time-consuming and thus not suitable for interactive image editing systems.…”

Section: Pigment-based Featuresmentioning

confidence: 99%

“…Both types of weights are influenced by the roughness of the paper. The roughness of the paper is modeled as a height field and is created using the method proposed by Curtis et al [3]. When the weights at pixel p are diffused to its neighboring pixel p , they are scaled by the factor of (1 + (height(p) − height(p )) where height(p) represents the height of paper at p.…”

Section: Rendering Strokes Using Color Diffusionmentioning

confidence: 99%

See 3 more Smart Citations

Creating Watercolor Style Images Taking Into Account Painting Techniques

Johan¹,

Hashimoto²,

Nishita³

2004

The Journal of the Society for Art and Science

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Research for creating impressive images like paintings has attained more and more importance because of the recent growth in processing images. Among many painting styles, watercolor style gives a strong impression because of its thin colors and its soft appearance. This paper proposes a method to create watercolor style images from input images, for instance photographs. In contrast with the previously proposed watercolor methods that focuses only on simulating the effects of watercolor medium such as the mottled appearance and the color glazing, the proposed method also considers how the watercolor paintings are painted in order to simulate artists' painting techniques. In the proposed method, artists' painting techniques are represented using painting rules. Several painting rules are provided, in addition, user can specify their own painting rules. These painting rules are used for generating strokes to paint the objects. Painting techniques are simulated by first detecting the objects in the input image and generating strokes for each object according to the painting rules. The properties of watercolor medium are simulated by approximating each stroke with sampling points and diffuses their color to nearby pixels. Using the proposed method, a user can interactively create watercolor style images.

show abstract

Section: Related Workmentioning

confidence: 98%

Section: Related Workmentioning

confidence: 99%

Section: Pigment-based Featuresmentioning

confidence: 99%

Section: Rendering Strokes Using Color Diffusionmentioning

confidence: 99%

See 2 more Smart Citations

Creating Watercolor Style Images Taking Into Account Painting Techniques

Johan¹,

Hashimoto²,

Nishita³

2004

The Journal of the Society for Art and Science

View full text Add to dashboard Cite

show abstract

“…A wide variety of expressive styles [7,16,25] have been successfully applied to convert images in artistic styles such as Impressionism or Pointillism [41]. The typical NPR scenario aims to process a 2D image to create a stylized output.…”

Section: Related Workmentioning

confidence: 99%

Stroke-based splatting: an efficient multi-resolution point cloud visualization technique

et al. 2017

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Current state-of-the-art point cloud visualization techniques have shortcomings when dealing with sparse and less accurate data or close-up interactions. In this paper, we present a visualization technique called stroke-based splatting, which applies concepts of stroke-based rendering to surface-aligned splatting, allowing for better shape perception at lower resolutions and close-ups. We create a painterly depiction of the data with an impressionistic aesthetic, which is a metaphor the user is culturally trained to recognize, thus attributing higher quality to the visualization. This is achieved by shaping each object-aligned splat as a brush stroke, and orienting it according to globally coherent tangent vectors from the Householder formula, creating a painterly depiction of the scanned cloud. Each splat is sized according to a color-based clustering analysis of the data, ensuring the consistency of brush strokes within neighborhood areas. By controlling brush shape generation parameters and blend- ing factors between neighboring splats, the user is able to simulate different painting styles in real time. We have tested our method with data sets captured by commodity laser scanners as well as publicly available high-resolution point clouds, both having highly interactive frame rates in all cases. In addition, a user study was conducted comparing our approach to state-of-the-art point cloud visualization techniques. Users considered stroke-based splatting a valuable technique as it provides a higher or similar visual quality to current approaches.

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Painterly rendering techniques: a state‐of‐the‐art review of current approaches

Hegde

Gatzidis

Tian

2012

Computer Animation & Virtual

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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.

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Computer-generated watercolor

Cited by 368 publications

References 40 publications

Creating Watercolor Style Images Taking Into Account Painting Techniques

Creating Watercolor Style Images Taking Into Account Painting Techniques

Stroke-based splatting: an efficient multi-resolution point cloud visualization technique

Painterly rendering techniques: a state‐of‐the‐art review of current approaches

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