In this paper, we describe a set of 3D and 4D visualization tools and techniques for CORIE, a complex environmental observation and forecasting system (EOFS) for the Columbia River. The Columbia River, a complex and highly variable estuary, is the target of numerous cross-disciplinary ecosystem research projects and is at the heart of multiple sustainable development issues with long reaching implications for the Pacific Northwest. However, there has been until recently no comprehensive and objective system available for modeling this environment, and as a consequence, researchers and agencies have had inadequate tools for evaluating the effects of natural resource management decisions. CORIE was designed to address this gap and is a major step towards the vision of a scalable, multi-use, real-time EOFS. Although CORIE already had a rich set of visualization tools, most of them produced 2D visualizations and did not allow for interactive visualization. Our work adds advanced interactive 3D tools to CORIE, which can be used for further inspection of the simulated and measured data.

We describe a system for non-photorealistic rendering (NPR) of virtual environments. In real time, it synthesizes imagery of architectural interiors using stroke-based textures. We address the four main challenges of such a system — interactivity, visual detail, controlled stroke size, and frame-to-frame coherence — through image based rendering (IBR) methods. In a preprocessing stage, we capture photos of a real or synthetic environment, map the photos to a coarse model of the environment, and run a series of NPR filters to generate textures. At runtime, the system re-renders the NPR textures over the geometry of the coarse model, and it adds dark lines that emphasize creases and silhouettes. We provide a method for constructing non-photorealistic textures from photographs that largely avoids seams in the resulting imagery. We also offer a new construction, art-maps, to control stroke size across the images. Finally, we show a working system that provides an immersive experience rendered in a variety of NPR styles.

We present a method for applying complex textures to hand-drawn characters in cel animation. The method correlates features in a simple, textured, 3-D model with features on a hand-drawn figure, and then distorts the model to conform to the hand-drawn artwork. The process uses two new algorithms: a silhouette detection scheme and a depth-preserving warp. The silhouette detection algorithm is simple and efficient, and it produces continuous, smooth, visible contours on a 3-D model. The warp distorts the model in only two dimensions to match the artwork from a given camera perspective, yet preserves 3-D effects such as self-occlusion and foreshortening. The entire process allows animators to combine complex textures with hand-drawn artwork, leveraging the strengths of 3-D computer graphics while retaining the expressiveness of traditional handdrawn cel animation.