WU Ying, postgraduate, majors in measurement data processing, E-mail: 1434805442@qq.com
Current robust fitting algorithms are prone to failure in point cloud data with a high contamination rate. To solve this problem, we introduce a weight matrix in the plane fitting method based on eigenvalue decomposition, where the initial weight is determined based on the normal vector information of point cloud, thus reducing the influence of outliers. We further use the scale-adaptive method to enhance the robustness. The scale factor of this method gradually decreases as the number of iterations increases, effectively solving the problem of low breakdown ration of traditional M estimation. The experimental results show that the breakdown ratio of the proposed algorithm is higher than that of existing robust point cloud fitting methods, and it can accurately estimate plane parameters in the point cloud data with a high outlier ratio.
| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |