Abstract
We present a novel system for the interactive modeling of developmental climbing plants with an emphasis on efficient control and plausible physics response. A plant is represented by a set of connected anisotropic particles that respond to the surrounding environment and to their inner state. Each particle stores biological and physical attributes that drive growth and plant adaptation to the environment such as light sensitivity, wind interaction, and physical obstacles. This representation allows for the efficient modeling of external effects that can be induced at any time without prior analysis of the plant structure. In our framework we exploit this representation to provide powerful editing capabilities that allow to edit a plant with respect to its structure and its environment while maintaining a biologically plausible appearance. Moreover, we couple plants with Lagrangian fluid dynamics and model advanced effects, such as the breaking and bending of branches. The user can thus interactively drag and prune branches or seed new plants in dynamically changing environments. Our system runs in real-time and supports up to 20 plant instances with 25k branches in parallel. The effectiveness of our approach is demonstrated through a number of interactive experiments, including modeling and animation of different species of climbing plants on complex support structures.
Highlights
Vegetation plays a key role in increasing the realism of 3D scenes in various application domains ranging from entertainment to architectural design
Our particle-based representation allows for the modeling of external effects that can be induced at any time without prior analysis of the plant structure
We have presented a novel system for the interactive modeling of growing climbing plants
Summary
Vegetation plays a key role in increasing the realism of 3D scenes in various application domains ranging from entertainment to architectural design. While plant libraries are readily available and commonly used, content creators are often confronted with the need to obtain plant models that dynamically adapt to concrete, yet changing scenes. Designers require full control over all stages of the plant development to employ plants as part of the storytelling in their applications. A number of approaches have been proposed for realizing adaptive plants. Some approaches involve simulation of plant development via parallel string rewriting systems [PL90] where the exogenous flow is achieved by using environmentally-sensitive query modules [PJM94, MP96]. Other methods address the requirements of adapting plants to their environment via inverse procedural models [SPK∗14], competition for resources [RLP07, PHL∗09, LRBP12], or simulated adaptation [PSK∗12]
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