An Interactive Modeling Method for Real Trees Based on Sparse Images

Abstract

The invention relates to a method for real tree interactive modeling based on sparse images. The method comprises the steps that an interactive branch extracting and reconstructing module starts from the sequence of n images forming an angle of 90 degrees with an input overlay tree, data of two-dimensional center positions and the diameters of branch nodes of all levels are interactively compiled and stored in the image 1, a branch hierarchical structure is established, the image 1 is searched for the corresponding position of a main branch on the image n with the middle images 2 to n-1 serving as references, the corresponding position of the main branch is marked, interactive compilation is conducted on the image n, and depth information corresponding to the branch node of each level in the image 1 is determined; according to the extracted information of the two-dimensional center positions, the depths and the thicknesses of the branch nodes and based on a branch space bounding box, perspective correction is conducted; a final three-dimensional model is generated by a leaf generating module according to the phyllotaxis rule in the phytology. According to the method, the reconstructed tree model is similar to a real tree form, the topological structure of the branches can be well maintained, and three-dimensional reconstruction of the tree on a common accuracy level is achieved.

Description

technical field [0001] The invention relates to the field of computer graphics, in particular to an interactive modeling method for real trees based on sparse images. Background technique [0002] Trees are one of the most ubiquitous natural objects on the earth. The 3D modeling of trees in real environments has a wide range of applications in fields such as virtual reality, landscape design, 3D animation and games, and digital agriculture. In the fields of virtual reality, landscape design, 3D animation and games, the introduction of a 3D model of a real tree can greatly enhance the sense of reality and immersion of the scene; in the field of agriculture and forestry, the establishment of a 3D model of a real tree can avoid artificial The inefficiency and low accuracy of measuring tree parameters, such as diameter at breast height, tree height, topology, etc., can also provide important spatial information for robotic harvesting, robotic spraying, and virtual pruning. Howe...

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Problems solved by technology

[0004] Among them, the rule-based method can easily and quickly generate trees of different tree types, but there are grammatical rules abstraction, the generation rules of the model are difficult for non-professional users to grasp, and it is difficult to obtain the 3D model of a specific tree in the real environment; interactive In the modeling method, the user outlines the two-dimensional shape of the tree model and then interactively edits the three-dimensional model of the generated tree. This method provides users with convenient editing controls, and even users who are not familiar with the geometric rules of the tree can create high-quality tree model, but the proposed method does not consider the interactive editing on multiple real tree photos; the image-based method is to reconstruct the three-dimensional information of the tree from the tree image or image sequence taken in the real world, which can better reflect the The three-dimensional outline information of the real tree, but there are strict requirements on the number of images (≥16) and the shooting angle (≥120°); the method based on the laser scanning point cloud is to directly obtain the point cloud data of the tree through the laser scanning instrument, Then realize the three-dimensional reconstruction of the tree. This method has high reconstruction accuracy, but the obtained point cloud data needs to go through complex processing procedures such as denoising, background elimination, registration and topology reconstruction. In addition, laser scanning equipment is expensive and harmful to the environment. Disadvantages such as light sensitivity and slow processing speed

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