摘要
激光点云数据包含信息丰富、精度高,在森林演变、植物模型重构方面应用广泛。为提高树三维重构时的精度与真实感,提出一种基于实测点云数据的三维重构方法。首先,使用Kinect 2.0采集树的双面点云数据,在树根附近放置塑料标准球作为标记,使用人工标记法粗配与ICP算法精配相结合的方式对获取的双面点云数据进行配准,得到树完整的点云数据;其次,引入生长角度约束改进空间殖民算法生成树的三维骨架,根据管道模型估算树枝粗度,使用广义圆柱体生成树干;最后,对叶片单独建模,根据叶序规则添加树叶完成树的三维重构。以玉兰树、枫树以及Limit Tree为例进行重构试验,试验结果表明,该方法能够逼真地模拟树的三维形态结构,较好地展现树的拓扑结构关系,重构误差在6.5%以内,可为虚拟树木三维建模、虚拟修剪以及树的拓扑结构分析等研究提供参考。
Laser point cloud data contain detailed and high precision information,which is widely applied to forest evolution and plant reconstruction. In order to improve the accuracy and photorealistic in tree 3D reconstruction,a 3D reconstruction method based on point cloud was proposed. Firstly,the Kinect 2.0 was used for acquiring double face point cloud data of tree,and there were four plastic balls which were artificial markers near the tree. In the process of registration,artificial marker method and iterative closest point( ICP) algorithm were combined to merge point cloud data together accurately. Then,the complete point cloud data of tree can be obtained. Secondly,the improved space colonization algorithm was used with growth angle constraint to generate the 3D skeleton of tree,and then thickness of tree was estimated according to pipeline model,and the trunk was generated by generalized cylinder. Finally,leaves which were modeled based on point cloud data were added to branches according to phyllotaxis.Reconstruction experiment was performed by using magnolia,maple and limit tree data,which was provided by Visual Computing Research Center of Shenzhen Institutes of Advanced Technology( VCC).The reconstruction results showed that the proposed method can simulate 3D morphological structure of tree realistically and it showed the topological structure of trees well. Reconstructed tree models were plausible to the real-world trees and reconstruction error was less than 6.5%. Meanwhile,the proposed algorithm could be applied to the researches of three-dimensional modeling of virtual trees,virtual pruning experiment and tree topological structure analysis.
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2018年第2期207-216,共10页
Transactions of the Chinese Society for Agricultural Machinery
基金
国家高技术研究发展计划(863计划)项目(2013AA102304)
国家自然科学基金项目(61303124)
中央高校基本科研业务费专项资金项目(Z109021708)