Research on mining car target recognition method based on machine learning algorithms

In the process of acceptance measurement based on drone point cloud data, the mining cars in the open-pit mining area will generate a large number of pseudo terrain points in the 3D point cloud modeling process. If they are not extracted and removed, the accuracy of acceptance measurement will be seriously reduced. Therefore, how to accurately identify and extract mining car points from 3D point cloud data is the main technical issue for high-precision acceptance of mining sites based on unmanned aerial car oblique photogrammetry technology. Therefore, this article proposes a machine learning algorithm based method for extracting open-pit mining car point sets, which can effectively solve the problem of reduced acceptance accuracy caused by the existence of mining car point sets, thereby improving the accuracy of acceptance measurement. This provides important technical support for open-pit mining site acceptance measurement based on drone photogrammetry technology.