Power grid facility detection and static model reconstruction based on multi-view stereo vision reconstruction

Abstract Power grid facility detection and static model reconstruction are critical in power system management and planning. Traditional methods have such problems as low detection accuracy, and the reconstruction result is inaccurate. It is necessary to find an effective method for improving detection accuracy and reliability. In this paper, a multi-view stereo vision reconstruction method was proposed to improve the accuracy of power grid facility detection and static model reconstruction. The method used the image information of multiple views and stereo vision algorithms, and integrated image information from multiple views through the image depth analysis and feature detection of the stereo vision algorithm. Finally, the detection and 3D model of the power facility were accurately reconstructed. The experimental verification showed that the multi-view stereo vision reconstruction method had a better effect on detecting the power grid facility and the static model reconstruction. The accuracy and integrity of the facility detection were improved, and the false alarm and miss detection in the traditional method were reduced.