Style and abstraction in portrait sketching

Berger, Itamar; Shamir, Ariel; Mahler, Moshe; Carter, Elizabeth; Hodgins, Jessica K.

doi:10.1145/2461912.2461964

Cited by 110 publications

(109 citation statements)

References 29 publications

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“…Berger et al [3] learned models of stroke parameters from training examples which consisted of line sketches at four abstraction levels that were provided by seven artists. The method by Rosin and Lai [21] first stylises the image with abstracted regions of flat colours plus black and white lines [15].…”

Section: Related Workmentioning

confidence: 99%

Watercolour Rendering of Portraits

Rosin

Lai

2018

Image and Video Technology

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Abstract. Applying non-photorealistic rendering techniques to stylise portraits needs to be done with care, as facial artifacts are particularly disagreeable. This paper describes a technique for watercolour rendering that uses a facial model to preserve distinctive facial characteristics and reduce unpleasing distortions of the face, while maintaining abstraction and stylisation of the overall image, employing stylistic elements of watercolour such as edge darkening, wobbling, glazing and diffusion.

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Section: Related Workmentioning

confidence: 99%

Watercolour Rendering of Portraits

Rosin

Lai

2018

Image and Video Technology

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“…Tresset and Leymarie [23] present a robotic installation that produces sketches of people, but it is a "naive drawer" not capable of learning different styles. Berger et al [24] gather and analyze data from a number of artists as they sketch a human faces from a reference photograph, and then use the trained models to synthesize portrait sketches. PortraitSketch system [25] assists users to draw sketches by adjusting their strokes in real time to improve their aesthetic quality.…”

Section: Synthesizing Facial Sketchesmentioning

confidence: 99%

Data-Driven Synthesis of Cartoon Faces Using Different Styles

Zhang

Dong

et al. 2017

IEEE Trans. on Image Process.

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Abstract-This paper presents a data-driven approach for automatically generating cartoon faces in different styles from a given portrait image. Our stylization pipeline consists of two steps: an offline analysis step to learn about how to select and compose facial components from the databases; a runtime synthesis step to generate the cartoon face by assembling parts from a database of stylized facial components. We propose an optimization framework that, for a given artistic style, simultaneously considers the desired image-cartoon relationships of the facial components and a proper adjustment of the image composition. We measure the similarity between facial components of the input image and our cartoon database via image feature matching, and introduce a probabilistic framework for modeling the relationships between cartoon facial components. We incorporate prior knowledge about image-cartoon relationships and the optimal composition of facial components extracted from a set of cartoon faces to maintain a natural, consistent, and attractive look of the results. We demonstrate generality and robustness of our approach by applying it to a variety of portrait images and compare our output with stylized results created by artists via a comprehensive user study.Index Terms-Cartoon face, face stylization, data-driven synthesis, component-based modeling.Y. Zhang is with the National

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“…RealBrush [14] used scanned images of real natural media to synthesize the texture appearance of user strokes. A portrait sketching system by Berger et al [15] is capable Fig. 1 Given an input image (a) along with a few scribbles by the user (b), our system automatically extracts a concise line abstraction with coherence and structure lines depicting the edges of the petals and the shapes of the pistils (c, d).…”

Section: Related Workmentioning

confidence: 99%

User-guided line abstraction using coherence and structure analysis

Tsai

Lee

et al. 2017

Comp. Visual Media

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Line drawing is a style of image abstraction where the perceptual content of the image is conveyed using distinct straight or curved lines. However, extracting semantically salient lines is not trivial and mastered only by skilled artists. While many parametric filters have successfully extracted accurate and coherent lines, their results are sensitive to parameter choice and easily lead to either an excessive or insufficient number of lines. In this work, we present an interactive system to generate concise line abstractions of arbitrary images via a few user specified strokes. Specifically, the user simply has to provide a few intuitive strokes on the input images, including tracing roughly along edges and scribbling on the region of interest, through a sketching interface. The system then automatically extracts lines that are long, coherent and share similar textural structures to form a corresponding highly detailed line drawing. We have tested our system with a wide variety of images. Our experimental results show that our system outperforms state-of-the-art techniques in terms of quality and efficiency.

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Style and abstraction in portrait sketching

Cited by 110 publications

References 29 publications

Watercolour Rendering of Portraits

Watercolour Rendering of Portraits

Data-Driven Synthesis of Cartoon Faces Using Different Styles

User-guided line abstraction using coherence and structure analysis

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