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SF3M software: 3-D photo-reconstruction for non-expert users and its application to a gully network

机译:SF3M软件:面向非专业用户的3D图像重建及其在沟渠网络中的应用

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Three-dimensional photo-reconstruction (PR) techniques have been successfully used to produce high-resolution surface models for different applications and over different spatial scales. However, innovative approaches are required to overcome some limitations that this technique may present for field image acquisition in challenging scene geometries. Here, we evaluate SF3M, a new graphical user interface for implementing a complete PR workflow based on freely available software (including external calls to VisualSFM and CloudCompare), in combination with a low-cost survey design for the reconstruction of a several-hundred-metres-long gully network. SF3M provided a semi-automated workflow for 3-D reconstruction requiring ~ 49 h (of which only 17 % required operator assistance) for obtaining a final gully network model of > 17 million points over a gully plan area of 4230 m2. We show that a walking itinerary along the gully perimeter using two lightweight automatic cameras (1 s time-lapse mode) and a 6 m long pole is an efficient method for 3-D monitoring of gullies, at a low cost (~ EUR 1000 budget for the field equipment) and the time requirements (~ 90 min for image collection). A mean error of 6.9 cm at the ground control points was found, mainly due to model deformations derived from the linear geometry of the gully and residual errors in camera calibration. The straightforward image collection and processing approach can be of great benefit for non-expert users working on gully erosion assessment.
机译:三维光重建(PR)技术已成功用于产生针对不同应用和不同空间比例的高分辨率表面模型。但是,需要创新的方法来克服此技术可能会带来的一些局限性,以便在具有挑战性的场景几何图形中进行野外图像采集。在这里,我们评估SF3M,这是一个新的图形用户界面,用于基于免费软件(包括对VisualSFM和CloudCompare的外部调用)实施完整的PR工作流程,并结合低成本的调查设计来重建数百个米长的沟壑网络。 SF3M为3-D重建提供了一个半自动化的工作流程,需要约49小时(其中只有17%的操作员需要协助)才能在4230平方米的沟壑规划区域中获得> 1700万点的最终沟壑网络模型。我们证明了使用两个轻巧的自动摄像头(1 s延时模式)和一个6 m长的撑杆沿着沟壑周边行走的路线,是低成本,3D监测沟壑的有效方法(预算约为1000欧元)对于现场设备)和时间要求(对于图像采集,大约需要90分钟)。发现地面控制点的平均误差为6.9 cm,这主要归因于从沟壑的线性几何结构衍生出的模型变形以及相机校准中的残留误差。对于从事沟壑侵蚀评估的非专家用户而言,直接的图像收集和处理方法可能会非常有用。

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