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Reviewer: Diomidis Spinellis

Computer graphics has, from its inception, been dominated by a quest for realism: the generation of synthetic pictures that resemble the appearance of real images as much as possible. The painstaking modeling of physical illumination processes has resulted in fascinating synthetic images that are often indistinguishable from reality. Few human-made images, however, are drawn with this goal in mind. Paintings, drawings, and scientific illustrations are foremost communication tools, made to be beautiful, to give rise to emotions, or to efficiently convey information. Cognitive sciences, art, and graphic design play an important role in the creation of these images. Non-photorealistic rendering (NPR) uses processes that explicitly distance themselves from the goal of photographic accuracy to generate images that better communicate specific information. The applications of this kind of rendering are diverse, and range from engineering and medical illustrations to cartoon images. This work seeks to bring research results and practical experience that have accumulated in the area of NPR from the work of computer graphics scientists in the last 20 years under one roof. It is an intellectually stimulating and thought-provoking book, which provides a scientific framework for a rapidly evolving and challenging area. The material could be used as a textbook in a graduate graphics course, as well as a guide for practitioners and researchers in the field. Keep in mind, however, that the different types of techniques presented in the book require a wide breadth of background knowledge in areas as diverse as signal processing, computational geometry, analysis, and discrete mathematics. The techniques used for NPR can be broadly separated into those modeling image artifacts that result from the manner or style in which a geometric model is rendered, and those modeling artifacts that result from the way the geometric model represents an original object. Different NPR methods seek to simulate pen-and-ink drawings, pencil sketches, painterly effects, diverse natural media, artistic techniques, deformation, and lightning. Many of the above effects are intelligently deconstructed into the processes that result in them; the description of how traditional Chinese Suibokuga paintings can be modeled using cellular automata is a tour de force in analytical thinking. Unfortunately, the analysis sometimes stops short of providing the corresponding pseudocode. The book is divided into chapters, covering the pixel manipulation of images; the generation of lines, curves, and strokes; the simulation of natural media and artistic techniques; stroke-based illustrations; data structures for modeling distance; geometric and lighting models; distortions; and applications. The discussion of the applications of NPR easily conveys the field’s importance. The applications presented in the book include the representation of motion in still images (think of speed lines in cartoons), architectural illustrations, rendering plants, illustrating medical and technical texts, and tactile rendering for blind people. The book’s last chapter is contributed by Kees van Overveld, and is modestly titled “A Conceptual Framework for NPR.” It manages to provide, in an admittedly dense writing style, a single conceptual framework that, going beyond NPR, covers human perception and cognition in a formal manner. Resembling the style of treatment of Michael Arbib’s classic, “Brains, Machines, and Mathematics” [1], the chapter discusses how human perception, communication, and vehicles of scientific discourse delicately balance the sometimes conflicting notions of truthfulness, comprehensibility, and relevance. Online Computing Reviews Service