F or a long time, line drawings have been a part of artistic expression (for example, any pencil or pen-and-ink drawing), scientific illustrations (medical or technical), or entertainment graphics (such as in comics). Hence, computer graphics researchers have extensively studied the automatic generation of such lines. In particular, the area of nonphotorealistic rendering has focused on two main directions of research in this respect: the generation of hatching that conveys illumination as well as texture in an image and the computation of outlines and silhouettes. Silhouettes play an important role in shape recognition because they provide one of the main cues for figure-to-ground distinction. However, since silhouettes are view dependent, they need to be determined for every frame of an animation. Finding an efficient way to accomplish this is nontrivial. Indeed, a variety of different algorithms exist that compute silhouettes for geometric objects. This article provides a guideline for developers who need to choose between one of these algorithms for his or her application. Here, we restrict ourselves to discussing only those algorithms that apply to polygonal models, because these are the most commonly used object representations in modern computer graphics. (For an algorithm to compute the silhouette for free-form surfaces see, for example, Elber and Cohen. 1) Thus, we can use all algorithms discussed here to take a polygonal mesh as input and compute the visible part of the silhouette as output. Some algorithms, however, can also help compute the silhouette only, without additional visibility culling. The silhouette's representation might vary depending on the algorithm class-that is, the silhouette might take the form of a pixel matrix or a set of analytic stroke descriptions.

A way to create effective stylized line drawings is to draw strokes that start and stop at visible portions along the silhouette of an object to be portrayed. In computer graphics to date, algorithms to extract silhouette edges are many, although putting these edges into a form such that stylized strokes may be applied to them has not been greatly covered, so that existing methods are either time‐consuming or presented vaguely. In this paper, we introduce an algorithm that takes a set of silhouette edges originating from polygonal meshes and efficiently computes the visible parts of the edges before connecting them to form long smooth silhouette strokes to which stylization algorithms may be effectively applied. Features of our algorithm that gain efficiency and accuracy over existing methods is that we directly exploit the analytic connectivity information of the mesh in combination with the available z‐buffer information during rendering, and filter artifacts in connected edges during the process to improve the visual quality of strokes after stylization. Categories and Subject Descriptors (according to ACM CCS): 1.3.3 [Computer Graphics]: Picture/Image Generation—Line and curve generation 1.3.7 [Computer Graphics]: Three‐Dimensional Graphics and Realism—Hidden line/surface removal

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Previous studies at the intersection between rendering and psychology have concentrated on issues such as realismand acuity. Although such results have been useful in informing development of realistic rendering techniques,studies have shown that the interpretation of images is influenced by factors that have little to do with realism. Inthis paper, we summarize a series of experiments, the most recent of which are reported in a separate paper, thatinvestigate affective (emotive) qualities of images. These demonstrate significant effects that can be utilized withininteractive graphics, particularly via non‐photorealistic rendering (NPR). We explain how the interpretation ofthese results requires a high‐level model of cognitive information processing, and use such a model to account forrecent empirical results on rendering and judgement. Categories and Subject Descriptors (according to ACM CCS): I.3.m [Computer Graphics]: Miscellaneous

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