活立木点云数据三维重建的难点是测量数据海量且庞杂散乱。就单株活立木个体样本而言,树木主干几何形状极其不规整,枝叶分生散乱,由地面激光雷达扫描得到的树干实测数据非常庞杂散乱。笔者提出了一种新的基于骨架提取的活立木枝干三维建模方法:首先,对地面激光雷达扫描获得的原始点云进行枝叶分离; 然后根据Dijkstra距离对枝干点云数据进行分段并提取每个连通部分的骨架; 再根据加权的匹配度连接骨架,得到整株活立木完整的骨架; 最后用圆柱体拟合出活立木枝干的模型。分别对含笑树和樱花树枝干进行了扫描分析,拟合出含笑树和樱花树的枝干三维模型,并对该算法的效率进行了分析。结果表明,此次研究所用方法在运行时间和占用内存上都优于以往其他方法。
Abstract
The difficulty of 3D modeling for standing trees is to simplify complex and scattered mass measurement data. In regard to individual standing tree sample, the geometric shape of trunk is extremely irregular and unstructured, branches and leaves grow optional and in dispersion, and the trunk measured point cloud data(PCD)obtained by the terrestrial laser scanning(TLS)LiDAR is extraordinary numerous and jumbled. In this paper, we propose a new skeleton-based 3D modeling method for tree branches based on terrestrial laser scanned PCD. Firstly, leaves and branches of the original PCD are separated using semi-supervised SVM classifier. Then, the PCD of branches are segmented according to Dijkstra distance, and the skeleton of each connected part is extracted. After calculating the weights of distance and angle by linear programming, the skeletons are connected according to the weighted matching degree. The complete skeletons of the whole tree are done, and the models are reconstructed by cylinder fitting. Experiments were carried out on Sakura and Michelia maudiae with the models reconstructed and the effectiveness of the algorithm analyzed. The results showed that the method used in this study is better than other previous methods in running time and occupying memory.
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基金
收稿日期:2014-07-30 修回日期:2015-02-11基金项目:国家自然科学基金项目(31300472); 江苏省自然科学基金项目(BK2012418); 江苏高校优势学科建设工程资助项目(PAPD); 国家重点基础研究发展计划(2012CB416904); 农业部儋州热带作物科学观测实验站开放课题 第一作者:张天安,硕士生。*通信作者:云挺,副教授。E-mail: niyunting@qq.com。引文格式:张天安,云挺,薛联凤. 基于地面激光雷达的活立木枝干三维建模[J]. 南京林业大学
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