International audienceThe automated computation of appropriate viewpoints in complex 3D scenes is a key problem in a number of computer graphics applications. In particular, crowd simulations create visually complex environments with many simultaneous events for which the computation of relevant viewpoints remains an open issue. In this paper, we propose a system which enables the conveyance of events occurring in complex crowd simulations. The system relies on Reynolds' model of steering behaviors to control and locally coordinate a collection of camera agents similar to a group of reporters. In our approach, camera agents are either in a scouting mode, searching for relevant events to convey, or in a tracking mode following one or more unfolding events. The key benefit, in addition to the simplicity of the steering rules, holds in the capacity of the system to adapt to the evolving complexity of crowd simulations by self-organizing the camera agents to track interesting events.Le placement automatique de caméra dans une scène 3D est un problème important en informatique graphique. En particulier, les simulations de foules produisent des scènes complexes pour lesquelles le choix du point de vue est un problème non résolu. Dans ce travail, nous présentons une approche permettant de déterminer le placement et le cadrage de plusieurs caméras évoluant dans une simulation de foule, de facon à montrer aux mieux les événements qui se déroulent dans la simulation. Outre sa simplicité, notre méthode présente l'avantage d'adapter automatiquement le comportement des caméras à la complexité de la scène

Although an important component of natural scenes, the representation of skyscapes is often relatively simplistic. This can be largely attributed to the complexity of the thermodynamics underpinning cloud evolution and wind dynamics, which make interactive simulation challenging. We address this problem by introducing a novel layered model that encompasses both terrain and atmosphere, and supports efficient meteorological simulations. The vertical and horizontal layer resolutions can be tuned independently, while maintaining crucial inter-layer thermodynamics, such as convective circulation and land-air transfers of heat and moisture. In addition, we introduce a cloud-form taxonomy for clustering, classifying and upsampling simulation cells to enable visually plausible, finely-sampled volumetric rendering. As our results demonstrate, this pipeline allows interactive simulation followed by up-sampled rendering of extensive skyscapes with dynamic clouds driven by consistent wind patterns. We validate our method by reproducing characteristic phenomena such as diurnal shore breezes, convective cells that contribute to cumulus cloud formation, and orographic effects from moist air driven upslope.

We present a novel, interactive interface for the integrated cleanup, neatening, structuring and vectorization of sketch imagery. Converting scanned raster drawings into vector illustrations is a wellresearched set of problems. Our approach is based on a Delaunay subdivision of the raster drawing. We algorithmically generate a colored grouping of Delaunay regions that users interactively refne by dragging and dropping colors. Sketch strokes defned as marking boundaries of diferent colored regions are automatically neatened using Bézier curves, and turned into closed regions suitable for