A unified scheme for adaptive stroke-based rendering

Kang, Hyung Seok; Chui, Charles K.; Chakraborty, Uday K.

doi:10.1007/s00371-006-0066-7

Cited by 32 publications

(10 citation statements)

References 31 publications

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“…These styles include painting [20,4,12,13,9,11,18], pen-and-ink illustration [29,28,30], pencil drawing [34,7], and engraving [25,7], where clean, accurate depiction of outlines is either unnecessary or relatively unimportant. Instead, they focus on filling the interior regions with certain types of 'strokes' (thus the term of strokebased rendering), such as lines, rectangles, or polygons, to stylistically describe the tonal variation across the surface.…”

Section: Stroke-based Renderingmentioning

confidence: 99%

“…Wen et al [37] also used mean-shift segmentation to produce a rough sketch of the scene. Fischer et al [8] and Kang et al [18] both employed Canny edge detector to obtain stylized augmented reality and line-based illustrations, respectively. Note in general edge detector is suitable for extracting lines while image segmentation is effective in pixel clustering.…”

Section: Image Abstractionmentioning

confidence: 99%

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Abstract Line Drawings from 2D Images

Mo¹,

Popescu²,

Wyman³

2007

15th Pacific Conference on Computer Graphics and Applications (PG'07)

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We present a novel scheme for automatically generating line drawings from 2D images, aiming to facilitate effective visual communication. In contrast to conventional edge detectors, our technique imitates the human line drawing process and consists of two parts: line extraction and line rendering. We propose a novel line extraction method based on likelihood-function estimation, which effectively finds the genuine shape boundaries. We consider the feature scale and the blurriness of lines with which the detail and the focus-level of lines are controlled in the rendering. We also employ stroke textures to provide a variety of illustration styles. Experimental results demonstrate that our technique generates various kinds of line drawings from 2D images enabled by the control over detail, focus, and style.

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Section: Stroke-based Renderingmentioning

confidence: 99%

Section: Image Abstractionmentioning

confidence: 99%

Abstract Line Drawings from 2D Images

Mo¹,

Popescu²,

Wyman³

2007

15th Pacific Conference on Computer Graphics and Applications (PG'07)

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“…Kang et al [19] proposed a system which uses the K-Means algorithm. It starts with a palette of colors selected from the input image by an initialization process which aims to collect sufficiently distinct colors.…”

Section: Color Reductionmentioning

confidence: 99%

A New NPR Approach for Image Stylization: Combining Edges, Color Reduction and Facial Exaggerations

Arruda

Porto

Alencar³

et al. 2008

2008 International Conference on Computational Intelligence for Modelling Control &Amp; Automation

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This paper presents an innovative nonphotorealistic rendering approach which combines three techniques for the stylization of digital images. These techniques consist of: (i) an existing state-of-the art edge-based sketching; (ii) a proposed novel color reduction and stylization process; and (iii) a proposed novel caricature generation process (when faces are visible). By comparing the outputs of the approach with existing photo-to-cartoon rendering systems, for a set of test images, it was possible to see that the appeal of the resulting images was noticeably better for the proposed approach.

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“…Rodrigues, du Buf and others [17][18] used human vision techniques to better tie visual perception theories to NPR and painterly rendering. Kang and others 16 introduce several techniques to adaptively generate stroke and other artistic parameters or attributes to tailor to a wide variety of SBR styles. Our research system uses a parameterized approach to approximate a knowledge domain for painterly rendering of portraits.…”

Section: Related Workmentioning

confidence: 99%

Painterly rendered portraits from photographs using a knowledge-based approach

DiPaola

2007

SPIE Proceedings

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Portrait artists using oils, acrylics or pastels use a specific but open human vision methodology to create a painterly portrait of a live sitter. When they must use a photograph as source, artists augment their process, since photographs have: different focusing -everything is in focus or focused in vertical planes; value clumping -the camera darkens the shadows and lightens the bright areas; as well as color and perspective distortion. In general, artistic methodology attempts the following: from the photograph, the painting must 'simplify, compose and leave out what's irrelevant, emphasizing what's important'. While seemingly a qualitative goal, artists use known techniques such as relying on source tone over color to indirect into a semantic color temperature model, use brush and tonal "sharpness" to create a center of interest, lost and found edges to move the viewers gaze through the image towards the center of interest as well as other techniques to filter and emphasize. Our work attempts to create a knowledge domain of the portrait painter process and incorporate this knowledge into a multispace parameterized system that can create an array of NPR painterly rendering output by analyzing the photographic-based input which informs the semantic knowledge rules.Keywords: Non Photorealistic Rendering, Stroke based Rendering, Painterly Rendering, Human Vision INTRODUCTIONNon Photorealistic Rendering (NPR) is a computer graphics technique which creates imagery with a wide variety of expressive styles inspired by painting, drawing, technical illustration, and cartoons. This is in contrast to typical computer graphics which focuses on photorealism. Within 3D and 2D NPR techniques, stroke based or painterly rendering typically uses a 2D source such as a photograph and creates a list of strokes to be rendered on a new canvas. NPR already has applications in video games, movies, architectural and technical illustration, animation and rising fields such as computational photography. NPR also has applications in learning and medicine (e.g. communication systems for autistic children) where filtering out un-needed detail is important, as is true in technical illustration.Since computer systems cannot typically hold a semantic representation of the object to be rendered (e.g. a face for a portrait, or an emotional emphasis), many current NPR techniques rely on computer imaging approaches (e.g. edge detection, image segmentation) that model at the physical level such as blobs, strokes and lines. We propose a novel approach to painterly rendering which relies on parameterizing a knowledge space of how a human painter paints -that is their open methodology to the process. In general, artistic methodology attempts the following: from the photograph or live sitter, the painting must 'simplify, compose and leave out what's irrelevant, emphasizing what's important'. Since human painters have knowledge of the source imagery, we are limiting this approach to portraiture and therefore take advantage of portrait and facial...

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A unified scheme for adaptive stroke-based rendering

Abstract: Abstract

Cited by 32 publications

References 31 publications

Abstract Line Drawings from 2D Images

Abstract Line Drawings from 2D Images

A New NPR Approach for Image Stylization: Combining Edges, Color Reduction and Facial Exaggerations

Painterly rendered portraits from photographs using a knowledge-based approach

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