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This paper presents the results of a study in which artists made line drawings intended to convey specific 3D shapes. The study was designed so that drawings could be registered with rendered images of 3D models, supporting an analysis of how well the locations of the artists ’ lines correlate with other artists’, with current computer graphics line definitions, and with the underlying differential properties of the 3D surface. Lines drawn by artists in this study largely overlapped one another (75 % are within 1mm of another line), particularly along the occluding contours of the object. Most lines that do not overlap contours overlap large gradients of the image intensity, and correlate strongly with predictions made by recent line drawing algorithms in computer graphics. 14 % were not well described by any of the local properties considered in this study. The result of our work is a publicly available data set of aligned drawings, an analysis of where lines appear in that data set based on local properties of 3D models, and algorithms to predict where artists will draw lines for new scenes.

Pen-and-ink line drawing techniques are frequently used to depict form, tone, and texture in artistic, technical, and scientific illustration. In non-photorealistic rendering (NPR), there has been considerable progress on reproducing traditional pen-and-ink techniques for rendering 3D objects. However, formal evaluation and validation of these NPR images remain an important open research problem. In this paper we present an observational study with three groups of users to examine their understanding and assessment of hand-drawn pen-and-ink illustrations of objects in comparison with NPR renditions of the same 3D objects. The results show that people perceive differences between those two types of illustration but that those that look computer-generated are still highly valued in terms of scientific illustration. CR Categories: I.3.0 [Computer Graphics]: General Keywords: Non-photorealistic rendering (NPR), evaluation of NPR and traditional scientific illustration, observational study, penand-ink illustration. 1

Many materials including water, plastic, and metal have specular surface characteristics. Specular reflections have commonly been considered a nuisance for the recovery of object shape. However, the way that reflections are distorted across the surface depends crucially on 3D curvature, suggesting that they could, in fact, be a useful source of information. Indeed, observers can have a vivid impression of, 3D shape when an object is perfectly mirrored (i.e., the image contains nothing but specular reflections). This leads to the question what are the underlying mechanisms of our visual system to extract this 3D shape information from a perfectly mirrored object. In this paper we propose a biologically motivated recurrent model for the extraction of visual features relevant for the perception of 3D shape information from images of mirrored objects. We qualitatively and quantitatively analyze the results of computational model simulations and show that bidirectional recurrent information processing leads to better results than pure feedforward processing. Furthermore, we utilize the model output to create a rough nonphotorealistic sketch representation of a mirrored object, which emphasizes image features that are mandatory for 3D shape perception (e.g., occluding contour and regions of high curvature). Moreover, this sketch illustrates that the model generates a representation of object features independent of the surrounding scene reflected in the mirrored object.

We consider the problem of depicting continuous-tone images using only black and white. Traditional solutions to this problem include halftoning, which approximates tones, and line drawing, which approximates edges. We introduce “artistic thresholding ” as a technique that attempts to depict forms in an image. We apply segmentation to a source image and construct a planar subdivision that captures segment connectivity. Our artistic thresholding algorithm is a combinatorial optimization over this graph. The optimization is controlled by parameters that can be tuned to achieve different artistic styles.

The craft of papercutting is part of the folk art traditions of cultures all over the world. From the point of view of computer graphics, papercutting can be seen as a method of composing bi-level images under a set of geometric connectivity constraints. In this paper, we present a technique for composing digital paper-cut designs. The elements of a design may be images, which are processed via a multilayer thresholding operation, or they may be procedurallygenerated arrangements of shapes. Elements are composed using a set of boolean operators that preserve connectivity. The resulting designs are well suited to being cut by a new generation of inexpensive computer peripherals. 1.

I argue that Non-Photorealistic Rendering (NPR) research will play a key role in the scientific understanding of visual art and illustration. NPR can contribute to scientific understanding of two kinds of problems: how do artists create imagery, and how do observers respond to artistic imagery? I sketch out some of the open problems, how NPR can help, and what some possible theories might look like. Additionally, I discuss the thorny problem of how to evaluate NPR research and theories.

We present an unsupervised system which takes digital photographs as input, and generates simplified, stylized vector data as output. The three component parts of our system are image-space stylization, edge tracing, and edge-based image reconstruction. The design of each of these components is specialized, relative to their state of the art equivalents, in order to improve their effectiveness when used in such a combined stylization / vectorization pipeline. We demonstrate that the vector data generated by our system is often both an effective visual simplification of the input photographs, and an effective simplification in the sense of memory efficiency, as judged relative to state of the art lossy image compression formats.

The ability to analyze and reproduce specific-person facial expression is an important multimedia content service for mobile communication. In this paper, a novel three-layer facial animation model is presented for generating the personalized facial sketch animation, and the three layers are motion sequence layer, the reference shape layer, and the painting shape layer. Based on the model, a facial sketch animation generator was implemented, allowing mobile subscribers to communicate using personalized facial sketch animations created from face snapshot taken by their phone’s camera. The sender takes a snapshot of someone’s face and transmits it to a multimedia content server, which then generates the specific-person facial sketch image or animation sequence. The server sends the image or animation to the receiver in multimedia message (MMS). The implementation of the generator architecture is low-cost and feasible for multimedia content service in mobile communication. 1.

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