3 research outputs found

    Venation Skeleton-Based Modeling Plant Leaf Wilting

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    A venation skeleton-driven method for modeling and animating plant leaf wilting is presented. The proposed method includes five principal processes. Firstly, a three-dimensional leaf skeleton is constructed from a leaf image, and the leaf skeleton is further used to generate a detailed mesh for the leaf surface. Then a venation skeleton is generated interactively from the leaf skeleton. Each vein in the venation skeleton consists of a segmented vertices string. Thirdly, each vertex in the leaf mesh is banded to the nearest vertex in the venation skeleton. We then deform the venation skeleton by controlling the movement of each vertex in the venation skeleton by rotating it around a fixed vector. Finally, the leaf mesh is mapped to the deformed venation skeleton, as such the deformation of the mesh follows the deformation of the venation skeleton. The proposed techniques have been applied to simulate plant leaf surface deformation resulted from biological responses of plant wilting

    Modelling and Simulation of Lily flowers using PDE Surfaces

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    This paper presents a partial differential equation (PDE)-based surface modelling and simulation framework for lily flowers. We use a PDE-based surface modelling technique to represent shape of a lily flower and PDE-based dynamic simulation to animate blossom and decay processes of lily flowers. To this aim, we first automatically construct the geometry of lily flowers from photos to obtain feature curves. Second, we apply a PDE-based surface modelling technique to generate sweeping surfaces to obtain geometric models of the flowers. Then, we use a physics-driven and data-based method and introduce the flower shapes at the initial and final positions into our proposed dynamic deformation model to generate a realistic deformation of flower blossom and decay. The results demonstrate that our proposed technique can create realistic flower models and their movements and shape changes against time efficiently with a small data size
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