Since plants constitute an important part of natural scene, plant modeling is widely studied in the field of virtual reality. Plant modeling is a process that shape information is gathered through scanner, camera, or interaction, and plant structure is constructed using methods in computer graphics. Due to structural complexity and botanical diversity, current methods for plant modeling are generally time-consuming and difficult to use for novices, and they can’t satisfy the actual applications in computer games and 3D films, in the aspects of visual effect and speed. In this paper, we present several simple methods for fast plant modeling according to application needs. The main work and contributions are as follows: 1. Two plant modeling methods based on perspective particle flows are put forward. One method is based on trace analysis and perspective particle flows and the other method is based on leaf apex and perspective particle flows. In each method, a 3D vector field is constructed from image registration and a plant skeleton is simulated through particle flows. The innovative idea of these techniques is that they combine visual reconstruction with particle flows, and use them for particles’ initial position computation and trace restriction. The shape and position of 3D branches are accordant with their input images. 2. A tree modeling method using depth retrieval is proposed. From sketches of users, main branches are constructed using depth retrieval, and within 2D crown silhouette, small branches are modeled based on the principle of self-similarity. A depth retrieval method is put forward. It resolves the problem of branch matching in two sketches, and constructs a 3D structure that keeps the shapes of both input sketches accurately. Some problems in current methods, such as narrow application range, lack of shape control for branches in leaves, and difference between model and inputs are avoided in our method. 3. A method for tree modeling by building skeleton point cloud is put forward. Based on the matching principle of same height and same position, a 3D skeleton point cloud is built from two sketches. Through searching matching point in the 3D point cloud, a 2D skeleton is converted into a 3D structure which satisfies the restriction of point cloud shape. The advantage of this method is that the problems of branch occlusion and matching are solved, and compared with current methods, modeling efficiency is improved. ...
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