岩体三维实景模型尺度与方位的高效校准

    Efficient calibration of the scale and orientation of the 3 D real scene model of the rock mass

    • 摘要: 基于岩体三维实景模型进行测量工作能够极大的提升测量效率,减少测量人员安全隐患,而岩体三维实景模型在方位和尺度上的高效校准,是实现高效、安全岩体测量工作的前提。针对岩体三维实景模型尺度与方位高效校准的问题,研究了基于运动推断结构(Structure from Motion,简称SFM)+多视图立体(Multi-View Stereo,简称MVS)算法重构围岩三维实景模型的方法,提出了以三标靶点和三轴陀螺仪相结合的岩体实景模型方位与尺度的校准方法,研制了可折叠三点式校准设备,并基于蓝牙通信协议研发了校准设备数据快速采集APP,以OpenGL图形库开发技术为基础开发了交互式实景模型校准软件系统。以某地表岩质边坡为例,进行了岩体实景模型的高效采集和校准,并使用自主研发的SlopeRMI软件对岩体结构实现了高效测量。结果表明:所研究的校准方法、设备、软件系统能够高效的实现岩体实景模型方位与尺度的校准,具有一定的应用前景。

       

      Abstract: The use of a 3D real-scene rock mass model for measurement tasks can significantly improve measurement efficiency and reduce safety risks for survey personnel. Efficient and accurate calibration of the orientation and scale of the 3D real-scene rock mass model is a prerequisite for achieving high-efficiency and safe rock mass measurement. To address the challenge of efficiently calibrating the scale and orientation of 3D real-scene rock mass models, this study investigated a method for reconstructing a 3D real-scene rock mass model based on the SFM (Structure from Motion) + MVS (Multi-View Stereo) algorithm. A calibration method combining three target points and a three-axis gyroscope was proposed to adjust the orientation and scale of the rock mass model. A foldable three-point calibration device was developed, and a data acquisition APP based on the Bluetooth communication protocol was designed for rapid data collection from the calibration device. Additionally, an interactive real-scene model calibration software system was developed using OpenGL graphics library technology. Taking a surface rock slope as an example, efficient data acquisition and calibration of the rock mass model were conducted, and the self-developed SlopeRMI software was employed to achieve efficient measurement of the rock mass structure. The results demonstrate that the proposed calibration method, device, and software system can effectively calibrate the orientation and scale of the rock mass model, showing promising application prospects.

       

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