This paper describes a method for inferring three-dimensional (3D) plant branch structures that are hidden under leaves from multi-view observations. Unlike previous geometric approaches that heavily rely on the visibility of the branches or use parametric branching models, our method makes statistical inferences of branch structures in a probabilistic framework. By inferring the probability of branch existence using a Bayesian extension of image-to-image translation applied to each of multi-view images, our method generates a probabilistic plant 3D model, which represents the 3D branching pattern that cannot be directly observed. Experiments demonstrate the usefulness of the proposed approach in generating convincing branch structures in comparison to prior approaches.
This paper describes the work done in creating a computer program capable of modelling rooted trees and in particular the branching structures of botanical and bronchial trees. Simplicity of design and flexibility of use was achieved by generalising the program to handle any rooted branching structure with the particular form being dictated by various controlling parameters which can be modified via a direct manipulation interface. The program provides a graphical display of the resultant tree and leaf distribution. The open skelet al design allows the user to tailor the program to a particular model and to easily access data derived by the model. This paper introduces a method for creating naturally varied plants from a given basic plant model. Previous techniques create variation in plants by introducing local randomness to the plant model's description. However, randomness is restricted by the model's parameterization and lack of correlation between local features making varying global properties (e.g. branch and stem curvature) difficult. We present a biologically−based method which mimics the underpinnings of variation in real plants. This method uses a feedback control system to simulate the biological growth mechanism by which a plant naturally responds to environmental factors. We show that our technique creates more realistically varied models by modelling growth responses to stimuli, and provides a method for quickly creating numerous similar models, none of which are exactly alike. Because of their complexity, plant models used in computer graphics are commonly created with proceduralmethods. A difficult problem is the user control of these models: a small number of parameters is insufficient tospecify plant characteristics in detail, while large numbers of parameters are tedious to manipulate and difficultto comprehend. To address this problem, we propose a method for managing parameters involved in plant modelmanipulation. Specifically, we introduce decomposition graphs as multiscale representations of plant structuresand present interactive tools for designing trees that operate on decomposition graphs. The supported operationsinclude browsing of the parameter space, editing of generalized parameters (scalars, functions, and branchingsystem silhouettes), and the definition of dependencies between parameters. We illustrate our method by creatingmodels of bonsai trees. We present a method for generating realistic models of temperate-climate trees and shrubs. This method is based on the biological hypothesis that the form of a developing tree emerges from a self-organizing process dominated by the competition of buds and branches for light or space, and regulated by internal signaling mechanisms. Simulations of this process robustly generate a wide range of realistic trees and bushes. The generated forms can be controlled with a variety of interactive techniques, including procedural brushes, sketching, and editing operations such as pruning and bending of branches. We illustrate the usefulness and versatility of the proposed method with diverse tree models, forest scenes, animations of tree development, and examples of combined interactive-procedural tree modeling. PG,1 An electrical connector for attaching an electrical cord to an electrical appliance is provided. The connector has an ejector which allows for one hand disengagement of the connector and cord from the appliance. The ejector has a first portion movable through and out of the connector and an integral hinge shaped second portion. By application of finger pressure on the second portion to flatten it, the first portion is moved out of the connector and against the appliance causing an oppositely directed movement of the connector, thereby disengaging the connector and cord from the appliance. We present a lobe-based tree representation for modeling trees. The new representation is based on the observation that the tree's foliage details can be abstracted into canonical geometry structures, termed lobe-textures. We introduce techniques to (i) approximate the geometry of given tree data and encode it into a lobe-based representation, (ii) decode the representation and synthesize a fully detailed tree model that visually resembles the input. The encoded tree serves as a light intermediate representation, which facilitates efficient storage and transmission of massive amounts of trees, e.g., from a server to clients for interactive applications in urban environments. The method is evaluated by both reconstructing laser scanned trees (given as point sets) as well as re-representing existing tree models (given as polygons). A method is proposed for photo-realistic modeling and visualization of a growing tree. Recent visualization methods have focused on producing smoothly blending branching structures, however, these methods fail to account for the inclusion of non-smooth features such as branch bark ridges and bud scale scars. These features constitute an important visual aspect of a living tree, and are also observed to vary over time. The proposed method incorporates these features by using an hierarchical implicit modeling system, which provides a variety of tools for combining surface components in both smooth and non smooth configurations. A procedural interface to this system supports the use of inverse modeling, which is a global-to-local methodology, where the local properties of plant organs are described in terms of their global position within the tree architecture. Inverse modeling is used to define both the tree structure at any time, and a continuous developmental sequence for the tree from a seedling. These techniques provide an intuitive paradigm for the definition of complex tree growth sequences and their subsequent visualization, based solely on observed phenomena. Thus, a key advantage is that they do not require any knowledge of, or simulation of, the underlying biological processes. Categories and Subject Descriptors (according to ACM CCS): I.3.5 [Computer Graphics]: Curve, surface, solid, and object representations I.3.7 [Computer Graphics]: Animation