34-Issue 7

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https://diglib.eg.org/handle/10.2312/13266

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Browsing 34-Issue 7 by Subject "I.3.3 [Computer Graphics]"

Now showing 1 - 6 of 6
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    Contrast-Enhanced Black and White Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Li, Hua; Mould, David; Stam, Jos and Mitra, Niloy J. and Xu, Kun
    This paper investigates contrast enhancement as an approach to tone reduction, aiming to convert a photograph to black and white. Using a filter-based approach to strengthen contrast, we avoid making a hard decision about how to assign tones to segmented regions. Our method is inspired by sticks filtering, used to enhance medical images but not previously used in non-photorealistic rendering. We amplify contrast of pixels along the direction of greatest local difference from the mean, strengthening even weak features if they are most prominent. A final thresholding step converts the contrast-enhanced image to black and white. Local smoothing and contrast enhancement balances abstraction and structure preservation; the main advantage of our method is its faithful depiction of image detail. Our method can create a set of effects: line drawing, hatching, and black and white, all having superior details to previous black and white methods.
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    Data-driven Handwriting Synthesis in a Conjoined Manner
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Chen, Hsin-I; Lin, Tse-Ju; Jian, Xiao-Feng; Shen, I-Chao; Chen, Bing-Yu; Stam, Jos and Mitra, Niloy J. and Xu, Kun
    A person's handwriting appears differently within a typical range of variations, and the shapes of handwriting characters also show complex interaction with their nearby neighbors. This makes automatic synthesis of handwriting characters and paragraphs very challenging. In this paper, we propose a method for synthesizing handwriting texts according to a writer's handwriting style. The synthesis algorithm is composed by two phases. First, we create the multidimensional morphable models for different characters based on one writer's data. Then, we compute the cursive probability to decide whether each pair of neighboring characters are conjoined together or not. By jointly modeling the handwriting style and conjoined property through a novel trajectory optimization, final handwriting words can be synthesized from a set of collected samples. Furthermore, the paragraphs' layouts are also automatically generated and adjusted according to the writer's style obtained from the same dataset. We demonstrate that our method can successfully synthesize an entire paragraph that mimic a writer's handwriting using his/her collected handwriting samples.
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    Efficient Variational Light Field View Synthesis For Making Stereoscopic 3D Images
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Zhang, Lei; Zhang, Yu-Hang; Huang, Hua; Stam, Jos and Mitra, Niloy J. and Xu, Kun
    We present a novel approach for making stereoscopic images by variational view synthesis on the multi-perspective light field. With the intended disparities as constraints, we specialize the generative variational model by incorporating per-pixel viewpoint assignment to synthesize the stereo pair. Also, we improve the variational solution by use of explicit weighted average on the light field. Our algorithm is able to handle arbitrary disparity remapping, thus enabling more flexible disparity control for the desired stereoscopic effect. The experiments demonstrate the effectiveness and efficiency for making the stereoscopic 3D images based on the light field.
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    Evaluating the Quality of Face Alignment without Ground Truth
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Sheng, Kekai; Dong, Weiming; Kong, Yan; Mei, Xing; Li, Jilin; Wang, Chengjie; Huang, Feiyue; Hu, Bao-Gang; Stam, Jos and Mitra, Niloy J. and Xu, Kun
    The study of face alignment has been an area of intense research in computer vision, with its achievements widely used in computer graphics applications. The performance of various face alignment methods is often imagedependent or somewhat random because of their own strategy. This study aims to develop a method that can select an input image with good face alignment results from many results produced by a single method or multiple ones. The task is challenging because different face alignment results need to be evaluated without any ground truth. This study addresses this problem by designing a feasible feature extraction scheme to measure the quality of face alignment results. The feature is then used in various machine learning algorithms to rank different face alignment results. Our experiments show that our method is promising for ranking face alignment results and is able to pick good face alignment results, which can enhance the overall performance of a face alignment method with a random strategy. We demonstrate the usefulness of our ranking-enhanced face alignment algorithm in two practical applications: face cartoon stylization and digital face makeup.
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    FlexyFont: Learning Transferring Rules for Flexible Typeface Synthesis
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Phan, Huy Quoc; Fu, Hongbo; Chan, Antoni B.; Stam, Jos and Mitra, Niloy J. and Xu, Kun
    Maintaining consistent styles across glyphs is an arduous task in typeface design. In this work we introduce Flexy- Font, a flexible tool for synthesizing a complete typeface that has a consistent style with a given small set of glyphs. Motivated by a key fact that typeface designers often maintain a library of glyph parts to achieve a consistent typeface, we intend to learn part consistency between glyphs of different characters across typefaces. We take a part assembling approach by firstly decomposing the given glyphs into semantic parts and then assembling them according to learned sets of transferring rules to reconstruct the missing glyphs. To maintain style consistency, we represent the style of a font as a vector of pairwise part similarities. By learning a distribution over these feature vectors, we are able to predict the style of a novel typeface given only a few examples. We utilize a popular machine learning method as well as retrieval-based methods to quantitatively assess the performance of our feature vector, resulting in favorable results. We also present an intuitive interface that allows users to interactively create novel typefaces with ease. The synthesized fonts can be directly used in real-world design.
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    Order-Independent Transparency for Programmable Deferred Shading Pipelines
    (The Eurographics Association and John Wiley & Sons Ltd., 2015) Schollmeyer, Andre; Babanin, Andrey; Froehlich, Bernd; Stam, Jos and Mitra, Niloy J. and Xu, Kun
    In this paper, we present a flexible and efficient approach for the integration of order-independent transparency into a deferred shading pipeline. The intermediate buffers for storing fragments to be shaded are extended with a dynamic and memory-efficient storage for transparent fragments. The transparency of an object is not fixed and remains programmable until fragment processing, which allows for the implementation of advanced materials effects, interaction techniques or adaptive fade-outs. Traversing costs for shading the transparent fragments are greatly reduced by introducing a tile-based light-culling pass. During deferred shading, opaque and transparent fragments are shaded and composited in front-to-back order using the retrieved lighting information and a physically-based shading model. In addition, we discuss various configurations of the system and further enhancements. Our results show that the system performs at interactive frame rates even for complex scenarios.