Building Tilt Scanning Measurement Based on Binary Linear Regression Analysis

Abstract

Abstract With the development of modern surveying and mapping technology, 3D laser scanners are increasingly used for building dip scanning. Building inclination characteristics are analyzed using three-dimensional point cloud data and binary linear regression. It can easily and intuitively obtain the inclination of the building. This method extracted the building inclination Angle from the point, line, plane, surface, and other angles. Then, a matching method based on two dimensions and surfaces is proposed, with a strong anti-noise ability. An optimal matching algorithm of structural plane and surface based on quadratic linear regression is proposed. Experiments prove the anti-interference ability and accuracy of this method. It is found that the binary linear regression fitting method can effectively identify the noise signal when there is a lot of noise interference in the point cloud data. It has good anti-interference ability.