Outliers in point clouds affect the performance of surface reconstruction directly. Most of outlier removal methods just remove those outliers far away from the real surface and are only applied to handle watertight s...Outliers in point clouds affect the performance of surface reconstruction directly. Most of outlier removal methods just remove those outliers far away from the real surface and are only applied to handle watertight surface. In this paper, a two-step outlier removal procedure is proposed to filter the point clouds acquired from the gray code and line-shifting technique. The first step is to remove the outliers far away from the real surface. Some feature points are extracted from the point clouds to construct an initial surface. The points with distances to the initial surface greater than a given threshold are removed as distant outliers. The retained points are linked into lines in each structured light sheet using their Voronoi diagrams. Some of lines which are very close to the real surface are removed as near outliers in the second step. The experimental results show that the proposed method is very effective in removing outliers for surface reconstruction.展开更多
基金the National Natural Science Foundation of China (No. 30470488)
文摘Outliers in point clouds affect the performance of surface reconstruction directly. Most of outlier removal methods just remove those outliers far away from the real surface and are only applied to handle watertight surface. In this paper, a two-step outlier removal procedure is proposed to filter the point clouds acquired from the gray code and line-shifting technique. The first step is to remove the outliers far away from the real surface. Some feature points are extracted from the point clouds to construct an initial surface. The points with distances to the initial surface greater than a given threshold are removed as distant outliers. The retained points are linked into lines in each structured light sheet using their Voronoi diagrams. Some of lines which are very close to the real surface are removed as near outliers in the second step. The experimental results show that the proposed method is very effective in removing outliers for surface reconstruction.
