360-degree three-dimensional reconstruction optimization method based on continuous phase dense matching

Abstract

The invention discloses a 360-degree three-dimensional reconstruction optimization method based on continuous phase dense matching. According to the method, 360-degree reconstruction of the three-dimensional point cloud of the measured object can be realized rapidly; a reconstruction result is subjected to nonlinear optimization; the method is realized through the following scheme: the method comprises the following steps: firstly, carrying out calibration of a digital projector and a camera; obtaining a corresponding structured light deformation image; calculating the phase order of the deformed fringe pixel points, and determining the epipolar lines of the deformed fringe pixel points in different camera imaging planes of the camera array at the same time, thereby establishing epipolar geometry and equiphase joint constraints, calculating the dense matching of structured light images at different viewing angles, and generating a phase dense matching relationship of the deformed fringe pixels at different angles; initializing a camera transformation matrix and a three-dimensional point cloud initial point by utilizing a phase dense matching relationship and a triangularization principle, constructing an objective function and a graph optimization model thereof, and solving the objective function and the graph optimization model; and performing triangulation surface reconstruction on the optimized three-dimensional point cloud to obtain a complete 360-degree three-dimensional target reconstruction model of the measured target.

Description

technical field [0001] The invention relates to a three-dimensional reconstruction technology, in particular to a 360° three-dimensional reconstruction optimization method based on continuous phase dense matching. Background technique [0002] 3D reconstruction is widely used in industrial production, reverse engineering, aerial survey, virtual reality and other fields. Based on the 3D reconstruction of structured light projection and image information, the extremely high-precision 3D information of the measured 3D object can be obtained. At the same time, the multi-view geometry principle of multi-camera or motion camera can be used to obtain a larger angle range and a more complete 3D model. Therefore, , the multi-camera structured light reconstruction method is an effective means to obtain a high-precision 360° complete 3D model. In the structured light reconstruction method, the registration of the 3D point cloud and the optimization of the reconstruction results are tw...

AI Technical Summary

Problems solved by technology

The 3D point cloud registration obtains the corresponding rigid body transformation relationship of multiple point clouds from different perspectives, but because there are various small fluctuation noises in the single point cloud, if you want to obtain a complete reconstruction model with higher accuracy, you need Finely adjust the spatial position of each point in each 3D point cloud, which cannot be achieved through rigid body transformation. Therefore, it is necessary to build an optimization model for the complete reconstruction of point cloud noise to optimize the reconstruction results

In order to obtain the 3D model of the entire object, when the 3D data of objects from different viewing angles are registered to the same reference coordinate system, the registration error will accumulate due to the constant change of the reference viewing angle.

Images