Abstract Many algorithms in Computer Graphics require to synthesize a pattern along a curve. This is for instance the case with line stylization, to decorate objects with elaborate patterns (chains, laces, scratches), or to synthesize curvilinear features such as mountain ridges, rivers or roads. We describe a simple yet effective method for this problem. Our method addresses the main challenge of maintaining the continuity of the pattern while following the curve. It allows some freedom to the synthesized pattern: It may locally diverge from the curve so as to allow for a more natural global result. This also lets the pattern escape areas of overlaps or fold‐overs. This makes our method particularly well suited to structured, detailed patterns following complex curves. Our synthesizer copies tilted pieces of the exemplar along the curve, following its orientation. The result is optimized through a shortest path search, with dynamic programming. We speed up the process by an efficient parallel implementation. Finally, since discontinuities may always remain we propose an optional post‐processing step optimally deforming neighboring pieces to smooth the transitions.

Abstract Procedural textures usually require spending time testing parameters to realize the diversity of appearances. This paper introduces the idea of a procedural texture preview: A single static image summarizing in a limited pixel space the appearances produced by a given procedure. Unlike grids of thumbnails our previews present a continuous image of appearances, analog to a map. The main challenge is to ensure that most appearances are visible, are allocated a similar pixel area, and are ordered in a smooth manner throughout the preview. To reach this goal, we introduce a new layout algorithm accounting simultaneously for these criteria. After computing a layout of appearances, we rely on by‐example texture synthesis to produce the final preview. We demonstrate our approach on a database of production‐level procedural textures.

Recent spatial hashing schemes hash millions of keys in parallel, compacting sparse spatial data in small hash tables while still allowing for fast access from the GPU. Unfortunately, available schemes suffer from two drawbacks: Multiple runs of the construction process are often required before success, and the random nature of the hash functions decreases access performance. We introduce a new parallel hashing scheme which reaches high load factor with a very low failure rate. In addition our scheme has the unique advantage to exploit coherence in the data and the access patterns for faster performance. Compared to existing approaches, it exhibits much greater locality of memory accesses and consistent execution paths within groups of threads. This is especially well suited to Computer Graphics applications, where spatial coherence is common. In absence of coherence our scheme performs similarly to previous methods, but does not suffer from construction failures. Our scheme is based on the Robin Hood scheme modified to quickly abort queries of keys that are not in the table, and to preserve coherence. We demonstrate our scheme on a variety of data sets. We analyze construction and access performance, as well as cache and threads behavior.

Textures are often reused on different surfaces in large virtual environments. This leads to unpleasing stretch and cropping of features when textures contain architectural elements. Existing retargeting methods could adapt each texture to the size of their support surface, but this would imply storing a different image for each and every surface, saturating memory. Our new texture synthesis approach casts synthesis as a shortest path problem in a graph describing the space of images that can be synthesized. Each path in the graph describes how to form a new image by cutting strips of the source image and reassembling them in a different order. Only the paths describing the result need to be stored in memory: synthesized textures are reconstructed at rendering time. The user can control repetition of features, and may specify positional constraints. We demonstrate our approach on a variety of textures, from facades for large city rendering to structured textures commonly used in video games.