Figure 1 An image analogy. Our problem is to compute a new “analogous ” image B ′ that relates to B in “the same way ” as A ′ relates to A. Here, A, A ′ , and B are inputs to our algorithm, and B ′ is the output. The full-size images are shown in Figures 10 and 11. This paper describes a new framework for processing images by example, called “image analogies. ” The framework involves two stages: a design phase, in which a pair of images, with one image purported to be a “filtered ” version of the other, is presented as “training data”; and an application phase, in which the learned filter is applied to some new target image in order to create an “analogous” filtered result. Image analogies are based on a simple multiscale autoregression, inspired primarily by recent results in texture synthesis. By choosing different types of source image pairs as input, the framework supports a wide variety of “image filter ” effects, including traditional image filters, such as blurring or embossing; improved texture synthesis, in which some textures are synthesized with higher quality than by previous approaches; super-resolution, in which a higher-resolution image is inferred from a low-resolution source; texture transfer, in which images are “texturized ” with some arbitrary source texture; artistic filters, in which various drawing and painting styles are synthesized based on scanned real-world examples; and texture-by-numbers, in which realistic scenes, composed of a variety of textures, are created using a simple painting interface.

Algorithms exist for synthesizing a wide variety of textures over rectangular domains. However, it remains difficult to synthesize general textures over arbitrary manifold surfaces. In this paper, we present a solution to this problem for surfaces defined by dense polygon meshes. Our solution extends Wei and Levoy's texture synthesis method [25] by generalizing their definition of search neighborhoods. For each mesh vertex, we establish a local parameterization surrounding the vertex, use this parameterization to create a small rectangular neighborhood with the vertex at its center, and search a sample texture for similar neighborhoods. Our algorithm requires as input only a sample texture and a target model. Notably, it does not require specification of a global tangent vector field; it computes one as it goes - either randomly or via a relaxation process. Despite this, the synthesized texture contains no discontinuities, exhibits low distortion, and is perceived to be similar to the sample texture. We demonstrate that our solution is robust and is applicable to a wide range of textures. Keywords: Texture Synthesis, Texture Mapping, Curves & Surfaces 1

In this paper, we propose a novel polygonal remeshing technique that exploits a key aspect of surfaces: the intrinsic anisotropy of natural or man-made geometry. In particular, we use curvature directions to drive the remeshing process, mimicking the lines that artists themselves would use when creating 3D models from scratch. After extracting and smoothing the curvature tensor field of an input geometry patch, lines of minimum and maximum curvatures are used to determine appropriate edges for the remeshed version in anisotropic regions, while spherical regions are simply point-sampled since there is no natural direction of symmetry locally. As a result our technique generates polygon meshes mainly composed of quads in anisotropic regions, and of triangles in spherical regions. Our approach provides the flexibility to produce meshes ranging from isotropic to anisotropic, from coarse to dense, and from uniform to curvature adapted.

Drawing surfaces using hatching strokes simultaneously conveys material, tone, and form. We present a real-time system for nonphotorealistic rendering of hatching strokes over arbitrary surfaces. During an automatic preprocess, we construct a sequence of mipmapped hatch images corresponding to different tones, collectively called a tonal art map. Strokes within the hatch images are scaled to attain appropriate stroke size and density at all resolutions, and are organized to maintain coherence across scales and tones. At runtime, hardware multitexturing blends the hatch images over the rendered faces to locally vary tone while maintaining both spatial and temporal coherence. To render strokes over arbitrary surfaces, we build a lapped texture parametrization where the overlapping patches align to a curvature-based direction field. We demonstrate hatching strokes over complex surfaces in a variety of styles. Keywords: non-photorealistic rendering, line art, multitexturing, chicken-and-egg problem 1

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We present a system that lets a designer directly annotate a 3D model with strokes, imparting a personal aesthetic to the non-photorealistic rendering of the object. The artist chooses a “brush ” style, then draws strokes over the model from one or more viewpoints. When the system renders the scene from any new viewpoint, it adapts the number and placement of the strokes appropriately to maintain the original look.

There are a number of applications in computer graphics that require as a first step the accurate estimation of principal direction vectors at arbitrary vertices on a triangulated surface. Although several methods for calculating principal directions over such models have been previously proposed, we have found in practice that all exhibit unexplained large errors in some cases. In this article, we describe our theoretical and experimental investigations into possible sources of errors in the approximation of principal direction vectors from triangular meshes, and suggest a new method for estimating principal directions that can yield better results under some circumstances.

We describe a way to render stylized silhouettes of animated 3D models with temporal coherence. Coherence is one of the central challenges for non-photorealistic rendering. It is especially difficult for silhouettes, because they may not have obvious correspondences between frames. We demonstrate various coherence effects for stylized silhouettes with a robust working system. Our method runs in real-time for models of moderate complexity, making it suitable for both interactive applications and offline animation.

This paper draws from art history and perception to place computer depiction in the broader context of picture production. It highlights the often underestimated complexity of the interactions between features in the picture and features of the represented scene. Depiction is not always a unidirectional projection from a 3D scene to a 2D picture, but involves much feedback and influence from the picture space to the object space. Depiction can be seen as a pre-existing 3D reality projected onto 2D, but also as a 2D pictorial representation that is superficially compatible with an hypothetic 3D scene. We show that depiction is essentially an optimization problem, producing the best picture given goals and constraints. We introduce a classification of basic depiction techniques based on four kinds of issue. The spatial system deals with the mapping of spatial properties between 3D and 2D (including, but not restricted to, perspective projection). The primitive system deals with the dimensionality and mappings between picture primitives and scene primitives. Attributes deal with the assignment of visual properties such as colors, texture, or thickness. Finally, marks are the physical implementations of the picture (e.g. brush strokes, mosaic cells). A distinction is introduced between interaction and picturegeneration methods, and techniques are then organized depending on the dimensionality of the inputs and outputs.