An Automatic Portrait System Based on And-Or Graph Representation

Min, Feng; Suo, Jinli; Zhu, Song‐Chun; Sang, Nong

doi:10.1007/978-3-540-74198-5_15

Cited by 18 publications

(8 citation statements)

References 14 publications

(13 reference statements)

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“…Its global design is very similar to that of Min et al [15], except a few differences in detailed algorithms, and that sketch examples in the latter are replaced by paper-cut versions in the former, as shown in Figure 11. Beside, Meng et al also used separated sub-systems for face, hair and the clothes.…”

Section: Paper-cutmentioning

confidence: 90%

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Artistic Rendering of Portraits

Zhao

Zhu

2012

Computational Imaging and Vision

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This chapter presents an overview of the latest artistic portrait rendering techniques. Artistic rendering or portraits can be viewed as an image generating process controlled by two factors. The first one is the face fidelity, namely, a rendered portrait image should preserve a certain amount of the original face's information. The second factor is the artistic style, for example, sketch, painting, etc. In the literature, different portrait rendering algorithms either adopt different models and data structures to represent the facial information, or use different graphical elements and compositional methods to simulate various styles. These two factors essentially reveal the two principles in portraiture, namely the pursuit of likeness and aesthetic.

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Section: Paper-cutmentioning

confidence: 90%

“…To improve the visual effects, Min et al [15] collected more stylish training examples in ∆ A and added two sub-systems for processing the hair and clothes, respectively. Figure 7 includes an example generated by their system.…”

Section: Hierarchical Modelmentioning

confidence: 99%

Artistic Rendering of Portraits

Zhao

Zhu

2012

Computational Imaging and Vision

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“…Gooch et al [10] create black-andwhite facial illustrations from photographs and then deform these facial illustrations to create caricatures which highlight and exaggerate representative facial features. Min et al [20] propose an automatic portrait system by leveraging the And-Or graph based on existing sketch templates. Wei et al [21] use a statistical model to represent and to generate face wrinkles.…”

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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“…Contours of the components are optimized to better fit the input face. The hair region is segmented separately, as model fitting cannot address hair extraction properly [7].…”

Section: Methodsmentioning

confidence: 99%

“…To address the shape-preserving necessity of cartoon face generation, most of the present systems employed either AAM [5,7,9,17] or a variation of ASM [6,15,18,19]. Generally, ASM shows better robustness to different conditions, as it searches through local regions oppose to the AAM, which uses models of holistic appearance.…”

Section: Feature Extractionmentioning

confidence: 99%

Component-Based Cartoon Face Generation

Nejad

Balafar

2016

Electronics

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Abstract:In this paper, we present a cartoon face generation method that stands on a component-based facial feature extraction approach. Given a frontal face image as an input, our proposed system has the following stages. First, face features are extracted using an extended Active Shape Model. Outlines of the components are locally modified using edge detection, template matching and Hermit interpolation. This modification enhances the diversity of output and accuracy of the component matching required for cartoon generation. Second, to bring cartoon-specific features such as shadows, highlights and, especially, stylish drawing, an array of various face photographs and corresponding hand-drawn cartoon faces are collected. These cartoon templates are automatically decomposed into cartoon components using our proposed method for parameterizing cartoon samples, which is fast and simple. Then, using shape matching methods, the appropriate cartoon component is selected and deformed to fit the input face. Finally, a cartoon face is rendered in a vector format using the rendering rules of the selected template. Experimental results demonstrate effectiveness of our approach in generating life-like cartoon faces.

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An Automatic Portrait System Based on And-Or Graph Representation

Cited by 18 publications

References 14 publications

Artistic Rendering of Portraits

Artistic Rendering of Portraits

Data-Driven Synthesis of Cartoon Faces Using Different Styles

Component-Based Cartoon Face Generation

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