240 research outputs found

    Stroke-Based Stylization Learning and Rendering with Inverse Reinforcement Learning

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    Among various traditional art forms, brush stroke drawing is one of the widely used styles in modern computer graphic tools such as GIMP, Photoshop and Painter. In this paper, we develop an AI-aided art authoring (A4) system of non- photorealistic rendering that allows users to automatically generate brush stroke paintings in a specific artist’s style. Within the reinforcement learning framework of brush stroke generation proposed by Xie et al.[Xie et al., 2012], our contribution in this paper is to learn artists’ drawing styles from video-captured stroke data by inverse reinforcement learning. Through experiments, we demonstrate that our system can successfully learn artists’ styles and render pictures with consistent and smooth brush strokes

    Beyond factual to formulated silhouettes

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    When sketching terrain, a view-dependent framework of silhouette-related cues is required. This framework is prominent in manual sketches and is especially important in small-scale depictions viewed obliquely from above. Occluding contours, namely the lines delineating depth discontinuities in the projected surface, are insufficient for forming this framework. The role which the occluding contour, or Factual Silhouette, plays in structuring the sketch becomes increasingly minimal as more of the terrain becomes visible, as the viewpoint is raised.The aim of this research is to extend the set of occluding contours to encompass situations that are perceived as causing an occlusion and would therefore be sketched in a similar manner. These locations, termed Formulated Silhouettes supplement the set of occluding contours and provide a successful structuring framework. The proposed method processes visible areas of terrain, which are turning away from view, to extract a classified, vector-based description for a given view of a Digital Elevation Model. Background approaches to silhouette rendering are reviewed and the specific contributions of this thesis are discussed.The method is tested using case studies composed of terrain of varying scale and character and two application studies demonstrate how silhouettes can be used to enhance existing terrain visualization techniques, both abstract and realistic. In addition, consultation with cartographic designers provides external verification of the research. The thesis concludes by noting how silhouette contours relate to perceived entities rather than actual occlusions

    Expressive rendering of mountainous terrain

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    technical reportPainters and cartographers have developed artistic landscape rendering techniques for centuries. Such renderings can visualize complex three-dimensional landscapes in a pleasing and understandable way. In this work we examine a particular type of artistic depiction, panorama maps, in terms of function and style, and we develop methods to automatically generate panorama map reminiscent renderings from GIS data. In particular, we develop image-based procedural surface textures for mountainous terrain. Our methods use the structural information present in the terrain and are developed with perceptual metrics and artistic considerations in mind

    Non-photorealistic rendering: a critical examination and proposed system.

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    In the first part of the program the emergent field of Non-Photorealistic Rendering is explored from a cultural perspective. This is to establish a clear understanding of what Non-Photorealistic Rendering (NPR) ought to be in its mature form in order to provide goals and an overall infrastructure for future development. This thesis claims that unless we understand and clarify NPR's relationship with other media (photography, photorealistic computer graphics and traditional media) we will continue to manufacture "new solutions" to computer based imaging which are confused and naive in their goals. Such solutions will be rejected by the art and design community, generally condemned as novelties of little cultural worth ( i.e. they will not sell). This is achieved by critically reviewing published systems that are naively described as Non-photorealistic or "painterly" systems. Current practices and techniques are criticised in terms of their low ability to articulate meaning in images; solutions to this problem are given. A further argument claims that NPR, while being similar to traditional "natural media" techniques in certain aspects, is fundamentally different in other ways. This similarity has lead NPR to be sometimes proposed as "painting simulation" — something it can never be. Methods for avoiding this position are proposed. The similarities and differences to painting and drawing are presented and NPR's relationship to its other counterpart, Photorealistic Rendering (PR), is then delineated. It is shown that NPR is paradigmatically different to other forms of representation — i.e. it is not an "effect", but rather something basically different. The benefits of NPR in its mature form are discussed in the context of Architectural Representation and Design in general. This is done in conjunction with consultations with designers and architects. From this consultation a "wish-list" of capabilities is compiled by way of a requirements capture for a proposed system. A series of computer-based experiments resulting in the systems "Expressive Marks" and 'Magic Painter" are carried out; these practical experiments add further understanding to the problems of NPR. The exploration concludes with a prototype system "Piranesi" which is submitted as a good overall solution to the problem of NPR. In support of this written thesis are : - • The Expressive Marks system • Magic Painter system • The Piranesi system (which includes the EPixel and Sketcher systems) • A large portfolio of images generated throughout the exploration

    Implementing non-photorealistic rendreing enhancements with real-time performance

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    We describe quality and performance enhancements, which work in real-time, to all well-known Non-photorealistic (NPR) rendering styles for use in an interactive context. These include Comic rendering, Sketch rendering, Hatching and Painterly rendering, but we also attempt and justify a widening of the established definition of what is considered NPR. In the individual Chapters, we identify typical stylistic elements of the different NPR styles. We list problems that need to be solved in order to implement the various renderers. Standard solutions available in the literature are introduced and in all cases extended and optimised. In particular, we extend the lighting model of the comic renderer to include a specular component and introduce multiple inter-related but independent geometric approximations which greatly improve rendering performance. We implement two completely different solutions to random perturbation sketching, solve temporal coherence issues for coal sketching and find an unexpected use for 3D textures to implement hatch-shading. Textured brushes of painterly rendering are extended by properties such as stroke-direction and texture, motion, paint capacity, opacity and emission, making them more flexible and versatile. Brushes are also provided with a minimal amount of intelligence, so that they can help in maximising screen coverage of brushes. We furthermore devise a completely new NPR style, which we call super-realistic and show how sample images can be tweened in real-time to produce an image-based six degree-of-freedom renderer performing at roughly 450 frames per second. Performance values for our other renderers all lie between 10 and over 400 frames per second on homePC hardware, justifying our real-time claim. A large number of sample screen-shots, illustrations and animations demonstrate the visual fidelity of our rendered images. In essence, we successfully achieve our attempted goals of increasing the creative, expressive and communicative potential of individual NPR styles, increasing performance of most of them, adding original and interesting visual qualities, and exploring new techniques or existing ones in novel ways.KMBT_363Adobe Acrobat 9.54 Paper Capture Plug-i

    Hybrid filter blending to maintain facial expressions in rendered human portraits

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    Artistic rendering of human portraits is different and more challenging than that of landscapes or flowers. Issues are eye, nose, and mouth regions (i.e., facial features) where we need to represent their natural emotions. Shades or darkness around eyes, or shininess at nose tips may negatively impact the rendering result if not properly dealt with. Similarly, a lighter colour around the mouth region caused by lighting might produce some disturbing artefacts. The proposed computerised method attempts to be adaptive to those sensitive areas by utilising a face analysis module. First, the program detects main facial segments and features. Then it utilises a blending of various filtering parameters aiming at an adequate final portrait that represents the subject's original facial expression, while still supporting a non-photorealistic artistic rendering as the perceived impression

    Interactive sketch generation

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