积雪深度3D识别与数字摄影测量

3D identification and digital photogrammetry of snow depths

摘要:

为解决传统积雪深度测量方法投入大、耗时长、效率低等问题,基于SfM（structure from motion）技术提出一种无接触式的高精度摄影测量技术,应用风雪联合试验系统针对不同模型进行风雪联合试验,利用相机获取积雪分布照片,还原雪面的三维坐标并利用MATLAB编程提取雪面的空间分布数据,与钢尺实测数据对比来评价该测量方法的精度.对比结果表明:利用摄影测量法对简单形式屋面进行测量时,能将绝对误差控制在±2 mm,相对误差在1%以内；测量复杂屋面时,绝对误差可控制在±4 mm,相对误差约为3%,测量精度满足模型试验测量要求,且利用摄影测量技术对复杂屋面积雪分布测量工作效率有显著提高.

Abstract:

To solve the problems of traditional snow depth measurement methods, such as large investment, time consuming, and low efficiency, a contactless method named Photogrammetry was proposed based on SfM (structure from motion). First, a series of experiments were conducted using the wind-snow combined experiment facility, and snow distribution photos were obtained by camera. Then, the three-dimensional coordinates of the snow surface were restored, and the spatial distribution data of the snow surface was extracted by MATLAB programming, which was compared with the snow depths that were measured by steel ruler to verify the accuracy of the method. The results showed that the accuracy was kept at ±2 mm and the relative error was within 1% when using photogrammetry for simple roofs. While when using photogrammetry for complex roofs, the accuracy was ±4 mm and the relative error was within 1%. It was proved that the accuracy of the photogrammetry method satisfied the measurement requirements of the tested model and the efficiency could be greatly improved when using photogrammetry for measuring snow depth distribution on complex test model roofs.