The placement of vegetation plays a central role in the realism of virtual scenes. We introduce procedural placement models (PPMs) for vegetation in urban layouts. PPMs are environmentally sensitive to city geometry and allow identifying plausible plant positions based on structural and functional zones in an urban layout. PPMs can either be directly used by defining their parameters or learned from satellite images and land register data. This allows us to populate urban landscapes with complex 3D vegetation and enhance existing approaches for generating urban landscapes. Our framework’s effectiveness is shown through examples of large-scale city scenes and close-ups of individually grown tree models. We validate the results generated with our framework with a perceptual user study and its usability based on urban scene design sessions with expert users.

Abstract We present an interactive method that allows users to easily abstract complex 3D models with only a few strokes. The key idea is to employ well‐known Gestalt principles to help generalizing user inputs into a full model abstraction while accounting for form, perceptual patterns and semantics of the model. Using these principles, we alleviate the user's need to explicitly define shape abstractions. We utilize structural characteristics such as repetitions, regularity and similarity to transform user strokes into full 3D abstractions. As the user sketches over shape elements, we identify Gestalt groups and later abstract them to maintain their structural meaning. Unlike previous approaches, we operate directly on the geometric elements, in a sense applying Gestalt principles in 3D. We demonstrate the effectiveness of our approach with a series of experiments, including a variety of complex models and two extensive user studies to evaluate our framework.

We present a framework to distribute point samples with controlled spectral properties using a regular lattice of tiles with a single sample per tile. We employ a word-based identification scheme to identify individual tiles in the lattice. Our scheme is recursive, permitting tiles to be subdivided into smaller tiles that use the same set of IDs. The corresponding framework offers a very simple setup for optimization towards different spectral properties. Small lookup tables are sufficient to store all the information needed to produce different point sets. For blue noise with varying densities, we employ the bit-reversal principle to recursively traverse sub-tiles. Our framework is also capable of delivering multi-class blue noise samples. It is well-suited for different sampling scenarios in rendering, including area-light sampling (uniform and adaptive), and importance sampling. Other applications include stippling and distributing objects.

We present a novel method for combining developmental tree models with turbulent wind fields. The tree geometry is created from internal growth functions of the developmental model and its response to external stress is induced by a physically-plausible wind field that is simulated by Smoothed Particle Hydrodynamics (SPH). Our tree models are dynamically evolving complex systems that (1) react in real-time to high-frequent changes of the wind simulation; and (2) adapt to long-term wind stress. We extend this process by wind-related effects such as branch breaking as well as bud abrasion and drying. In our interactive system the user can adjust the parameters of the growth model, modify wind properties and resulting forces, and define the tree's long-term response to wind. By using graphics hardware, our implementation runs at interactive rates for moderately large scenes composed of up to 20 tree models.

Given a static tree model we present a method to compute developmental stages that approximate the tree's natural growth. The tree model is analyzed and a graph-based description its skeleton is determined. Based on structural similarity, branches are added where pruning has been applied or branches have died off over time. Botanic growth models and allometric rules enable us to produce convincing animations from a young tree that converge to the given model. Furthermore, the user can explore all intermediate stages. By selectively applying the process to parts of the tree even complex models can be edited easily. This form of reverse engineering enables users to create rich natural scenes from a small number of static tree models.