Xiao Zhang
ABSTRACT
3D surface reconstruction is the basis of reconstructing real objects in virtual world, it is widely used in digital twin, virtual reality and other fields. Complex physical structure of objects, unnatural spatial geometry characteristics, shadow effect caused by radar scanning and the uneven light will cause the edge distortion and point cloud void when the virtual environment is generated in indoor environment. These problems will cause the accuracy of 3D model seriously decreased in the reconstruction process above. In order to solve this problem, this paper proposed a Robust Moving Least Squares (RMLS) algorithm based on boundary separation. The point cloud is projected onto a two-dimensional plane after feature extraction of the initial point cloud data; the boundary of point cloud is extracted by grid partitioning method, the boundary region and point cloud body are separated; the RMLS algorithm is implemented on the boundary point cloud obtained by separation to increase the number of data points in the boundary region; besides, combine the point cloud with the triangulation surface reconstruction algorithm. The solution of problems reduced the edge distortion, made up the point cloud void and improved the reconstruction accuracy.
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Index Terms
- Surface Reconstruction Based on Point Cloud Separation and Boundary RMLS
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