Measuring method of multiple trees attributes based on structure from motion
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摘要:
目的 提出基于运动恢复结构的多株立木因子测量方法，以解决目前基于三维点云的立木因子测量方法获取立木树高和胸径存在效率低或成本高的问题。 方法 ①使用智能手机环绕包含多株立木的场景拍摄一段视频，并采用固定帧采样法和差异值哈希算法自动提取立木视频中的关键帧图像，然后，基于运动恢复结构(structure from motion，SfM)算法处理立木关键帧图像，从而获取立木场景的原始三维点云；②在对原始三维点云进行预处理及初步分割后，运用条件欧几里得聚类算法对多株立木三维点云进行分割，以提取单株立木三维点云；③对立木三维点云使用最值遍历法和椭圆拟合法实现立木树高和胸径的自动测量。 结果 与真实值相比，本研究方法测得的树高、胸径的平均相对误差分别为1.96%、3.19%，均方根误差分别为0.133 3 m、0.533 7 cm，相关系数分别为0.987 9、0.962 1。 结论 该方法具有较高的树高和胸径测量精度，提供了一种便捷、低成本的多株立木因子三维测量方法。图6表1参27 Abstract:Objective Tree attributes are generally measured by obtaining the tree height and DBH using a method based on three-dimensional point cloud, which is featured with either low efficiency or high cost. To solve this problem, this study is aimed to propose a measuring method of multiple trees attributes based on Structure from Motion. Method Firstly, a smart phone was used to shoot a video of a scene with multiple trees before its key frame images were automatically extracted using the fixed-frame sampling and dHash algorithm; Secondly, such key frame images of the trees were processed on the basis of Structure from Motion (SfM) algorithm to obtain the original 3D point cloud of the scene; Thirdly, after the pre-procession and initial segmentation of the original 3D point cloud, the conditional European clustering algorithm is used to segment the 3D point cloud of multiple trees to extract the 3D point cloud of a single tree; Finally, the most value traversal method and ellipse fitting method were employed to deal with the tree 3D point cloud to realize the automatic measurement of tree height and DBH. Result Compared with real values, the mean relative errors of tree height and DBH measured using this method are 1.96% and 3.19%, the root mean square errors were 0.1333 m and 0.5337 cm whereas the correlation coefficients were 0.9879 and 0.9621 respectively. Conclusion This method, with high measurement accuracy of tree height and DBH, serves as a convenient and low-cost three-dimensional measurement method for multiple trees attributes. [Ch, 6 fig. 1 tab. 27 ref.] -
图 6 树高和胸径的测量值与实际值的回归分析
Figure 6 Regression analysis of measured and actual values of tree height and DBH
表 1 树高和胸径的测量值与实际值
Table 1. Measured and actual values of tree height and DBH
立木
编号树高 胸径 实际
值/m测量
值/m相对误
差/%实际
值/cm测量
值/cm相对误
差/%1 6.14 6.10 0.63 15.60 14.85 4.85 2 4.98 4.87 2.15 13.06 13.33 2.07 3 5.49 5.53 0.84 12.74 13.00 2.09 4 5.64 5.49 2.60 14.97 15.58 4.06 5 3.42 3.39 0.93 10.83 10.62 1.87 6 3.49 3.55 1.69 12.26 13.11 6.91 7 4.53 4.40 2.78 12.90 12.25 4.99 8 4.31 4.21 2.39 14.33 14.09 1.70 9 6.65 6.60 0.71 19.43 19.14 1.44 10 6.19 6.08 1.79 18.63 19.35 3.87 11 7.17 6.93 3.40 18.80 18.42 1.94 12 5.63 5.73 1.67 18.72 19.39 3.58 13 7.52 7.35 2.18 16.97 17.27 1.77 14 7.47 7.20 3.56 19.04 18.59 2.37 15 5.58 5.69 1.93 15.13 14.36 5.08 16 5.01 5.05 0.64 11.94 12.20 2.16 17 5.41 5.27 2.57 12.67 12.46 1.68 18 7.18 6.98 2.78 16.08 16.88 4.93 平均值 1.96 3.19 
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