Weighted Multiple Point Cloud Fusion

Multiple viewpoint 3D reconstruction has been used in recent years to create accurate complete scenes and objects used for various applications. This is to overcome limitations of single viewpoint 3D digital imaging such as occlusion within the scene during the reconstruction process. In this paper, we propose a weighted point cloud fusion process using both local and global spatial information of the point clouds to fuse them together. The process aims to minimize duplication and remove noise while maintaining a consistent level of details using spatial information from point clouds to compute a weight to fuse them. The algorithm improves the overall accuracy of the fused point cloud while maintaining a similar degree of coverage comparable with state-of-the-art point cloud fusion algorithms.