Sören Pirk

Plastic trees: interactive self-adapting botanical tree models

We present a dynamic tree modeling and representation technique that allows complex tree models to interact with their environment. Our method uses changes in the light distribution and proximity to solid obstacles and other trees as approximations of biologically motivated transformations on a skeletal representation of the trees main branches and its procedurally generated foliage. Parts of the tree are transformed only when required, thus our approach is much faster than common algorithms such as Open L-Systems or space colonization methods. Input is a skeleton-based tree geometry that can be computed from common tree production systems or from reconstructed laser scanning models. Our approach enables content creators to directly interact with trees and to create visually convincing ecosystems interactively. We present different interaction types and evaluate our method by comparing our transformations to biologically based growth simulation techniques.

Inverse Procedural Modelling of Trees

Procedural tree models have been popular in computer graphics for their ability to generate a variety of output trees from a set of input parameters and to simulate plant interaction with the environment for a realistic placement of trees in virtual scenes. However, defining such models and their parameters is a difficult task. We propose an inverse modelling approach for stochastic trees that takes polygonal tree models as input and estimates the parameters of a procedural model so that it produces trees similar to the input. Our framework is based on a novel parametric model for tree generation and uses Monte Carlo Markov Chains to find the optimal set of parameters. We demonstrate our approach on a variety of input models obtained from different sources, such as interactive modelling systems, reconstructed scans of real trees and developmental models.

Windy trees: computing stress response for developmental tree models

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 trees 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.

Image stylization with a painting machine using semantic hints

In this paper we present and evaluate painterly rendering techniques that work within a visual feedback loop of eDavid, our painting robot. The machine aims at simulating the human painting process. Two such methods and their semantics-driven combination are compared for different objects. One uses a predefined set of stroke candidates, the other creates strokes directly using line integral convolution. The aesthetics of these methods are discussed and results are shown. Graphical abstractSemantic and image feature driven combination of painterly rendering techniques that work within a visual feedback loop of eDavid, our painting robot.Display Omitted Highlights? We use visual feedback to create drawings from input pictures with a painting machine. ? We present two different drawing styles: Predefined strokes and dynamically generated strokes. ? We combine these styles according to its representation capabilities, semantic hints and image region features.

Feedback-guided stroke placement for a painting machine

In this paper we present and evaluate painterly rendering techniques that work within a visual feedback loop of eDavid, our painting robot. The machine aims at simulating the human painting process. Two such methods are compared for different objects. One uses a predefined set of stroke candidates, the other creates strokes directly using line integral convolution. The aesthetics of both methods are discussed, results are shown.

Video enhanced gigapixel panoramas

We present a method for embedding video clips within gigapixel scale imagery. The combination of high-resolution imagery and video enables users to pan and zoom across the gigapixel panorama to explore complex scenes with motion. The sparsity of the video content within the gigapixel context introduces several challenges which we overcome by optimizing the traversal of the scene coupled with appropriate playback of the embedded video. We also discuss aligning the video clips both geometrically and photometrically to reduce visible seams between the dynamic and static content. Embedding video in large scale panoramas fills a gap between static gigapixel images and video footage and thus presents a new interactive medium.

Improved model- and view-dependent pruning of large botanical scenes

We present an optimized pruning algorithm that allows for considerable geometry reduction in large botanical scenes while maintaining high and coherent rendering quality. We improve upon previous techniques by applying model‐specific geometry reduction functions and optimized scaling functions. For this we introduce the use of Precision and Recall (PR) as a measure of quality to rendering and show how PR‐scores can be used to predict better scaling values. We conducted a user‐study letting subjects adjust the scaling value, which shows that the predicted scaling matches the preferred ones. Finally, we extend the originally purely stochastic geometry prioritization for pruning to account for view‐optimized geometry selection, which allows to take global scene information, such as occlusion, into consideration. We demonstrate our method for the rendering of scenes with thousands of complex tree models in real‐time.

Understanding and Exploiting Object Interaction Landscapes

Interactions play a key role in understanding objects and scenes for both virtual and real-world agents. We introduce a new general representation for proximal interactions among physical objects that is agnostic to the type of objects or interaction involved. The representation is based on tracking particles on one of the participating objects and then observing them with sensors appropriately placed in the interaction volume or on the interaction surfaces. We show how to factorize these interaction descriptors and project them into a particular participating object so as to obtain a new functional descriptor for that object, its interaction landscape, capturing its observed use in a spatiotemporal framework. Interaction landscapes are independent of the particular interaction and capture subtle dynamic effects in how objects move and behave when in functional use. Our method relates objects based on their function, establishes correspondences between shapes based on functional key points and regions, and retrieves peer and partner objects with respect to an interaction.

Woodification: User-Controlled Cambial Growth Modeling

We present a botanical simulation of secondary (cambial) tree growth coupled to a physical cracking simulation of its bark. Whereas level set growth would use a fixed resolution voxel grid, our system extends the deformable simplicial complex (DSC), supporting new biological growth functions robustly on any surface polygonal mesh with adaptive subdivision, collision detection and topological control. We extend the DSC with temporally coherent texturing, and surface cracking with a user‐controllable biological model coupled to the stresses introduced by the cambial growth model.

Modeling plant life in computer graphics

1 Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s). An introduction to plant modeling and recent advances in plant modeling in computer graphics. Recent years have seen a lot of progress in vegetation modeling We focus on the following three areas 1) Procedural and biological modeling 2) Reconstruction and inverse procedural modeling 3) User-assisted models 3