NPAR15

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https://diglib.eg.org/handle/10.2312/12611

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Browsing NPAR15 by Title

Now showing 1 - 5 of 5
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    Drawing Characteristics for Reproducing Traditional Hand-Made Stippling
    (The Eurographics Association, 2015) Martín, Domingo; Sol, Vicente del; Romo, Celia; Isenberg, Tobias; David Mould and Pierre Bénard
    We contribute an in-depth analysis of the characteristics of traditional stippling and relate these to common practices in NPAR stippling techniques as well as to the abilities and limitations of existing printing and display technology. In our work we focus specifically on the properties of stipple dots and consider the dimensions and attributes of pens and paper types used in artistic practice. With our analysis we work toward an understanding of the requirements for digital stippling, with the ultimate goal to provide tools to artists and illustrators that can replicate the stippling process faithfully in the digital domain. From the results of our study we provide a dataset for use in new example-based stippling techniques, derive a taxonomy of characteristics and conditions for the reproduction of stippling, and define future directions of work.
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    Hybrid-Space Localized Stylization Method for View-Dependent Lines Extracted from 3D Models
    (The Eurographics Association, 2015) Cardona, Luis; Saito, Suguru; David Mould and Pierre Bénard
    We propose a localized stylization method that combines object-space and image-space techniques to locally styl- ize view-dependent lines extracted from 3D models. In the input phase, the user can customize a style and draw strokes by tracing over view-dependent feature lines such as occluding contours and suggestive contours. For each stroke drawn, the system stores its style properties as well as its surface location on the underlying polygonal mesh as a data structure referred as registered stroke. In the rendering phase, a new attraction field leads active contours generated from the registered strokes to match current frame feature lines and maintain the style and path coordinates of strokes in nearby viewpoints. For each registered stroke, a limited surface region referred as influence area is used to improve the line matching accuracy and discard obvious mismatches. The proposed styl- ization system produces uncluttered line drawings that convey additional information such as material properties or feature sharpness and is evaluated by measuring its usability and performance.
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    The Markov Pen: Online Synthesis of Free-Hand Drawing Styles
    (The Eurographics Association, 2015) Lang, Katrin; Alexa, Marc; David Mould and Pierre Bénard
    Learning expressive curve styles from example is crucial for interactive or computer-based narrative illustrations. We propose a method for online synthesis of free-hand drawing styles along arbitrary base paths by means of an autoregressive Markov Model. Choice on further curve progression is made while drawing, by sampling from a series of previously learned feature distributions subject to local curvature. The algorithm requires no useradjustable parameters other than one short example style. It may be used as a custom ''random brush'' designer in any task that requires rapid placement of a large number of detail-rich shapes that are tedious to create manually.
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    Semi-Automatic Digital Epigraphy from Images with Normals
    (The Eurographics Association, 2015) Berkiten, Sema; Fan, Xinyi; Rusinkiewicz, Szymon; David Mould and Pierre Bénard
    We present a semi-automated system for converting photometric datasets (RGB images with normals) into geometry-aware non-photorealistic illustrations that obey the common conventions of epigraphy (black-and-white archaeological drawings of inscriptions). We focus on rock inscriptions formed by carving into or pecking out the rock surface: these are characteristically rough with shallow relief, making the problem very challenging for previous line drawing methods. Our system allows the user to easily outline the inscriptions on the rock surface, then segment out the inscriptions and create line drawings and shaded renderings in a variety of styles. We explore both constant-width and tilt-indicating lines, as well as locally shape-revealing shading. Our system produces more understandable illustrations than previous NPR techniques, successfully converting epigraphy from a manual and painstaking process into a user-guided semi-automatic process.
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    Texture-Aware ASCII Art Synthesis with Proportional Fonts
    (The Eurographics Association, 2015) Xu, Xuemiao; Zhong, Linyuan; Xie, Minshan; Qin, Jing; Chen, Yilan; Jin, Qiang; Wong, Tien-Tsin; Han, Guoqiang; David Mould and Pierre Bénard
    We present a fast structure-based ASCII art generation method that accepts arbitrary images (real photograph or hand-drawing) as input. Our method supports not only fixed width fonts, but also the visually more pleasant and computationally more challenging proportional fonts, which allows us to represent challenging images with a variety of structures by characters. We take human perception into account and develop a novel feature extraction scheme based on a multi-orientation phase congruency model. Different from most existing contour detection methods, our scheme does not attempt to remove textures as much as possible. Instead, it aims at faithfully capturing visually sensitive features, including both main contours and textural structures, while suppressing visually insensitive features, such as minor texture elements and noise. Together with a deformation-tolerant image similarity metric, we can generate lively and meaningful ASCII art, even when the choices of character shapes and placement are very limited. A dynamic programming based optimization is proposed to simultaneously determine the optimal proportional-font characters for matching and their optimal placement. Experimental results show that our results outperform state-of-the-art methods in term of visual quality.